- Corpora - ELRA lists

First International Conference on Natural Language Processing
by Dola Mullage, Damith P. 19 Oct '23

19 Oct '23

First International Conference on Natural Language Processing and Artificial Intelligence for Cyber Security (NLPAICS’2024) Lancaster University, Lancaster 29-30 July 2024 First announcement Recent advances in Natural Language Processing (NLP), Deep Learning and Large Language Models have resulted in improved performance of applications benefiting from these techniques. In particular, in there has been a growing interest of employing AI methods in different Cyber Security applications. In today's digital world Cyber Security has emerged and its importance has magnified, becoming a priority for both individual users and organisations. With the exponential growth of the volume of information online, traditional security approaches often fall short in identifying and preventing evolving security threats. The inadequacy of conventional security frameworks highlights the need for innovative solutions that can effectively navigate the complex digital landscape for ensuring robust security. NLP and AI in Cyber Security have vast potential to significantly enhance threat detection and mitigation by fostering the development of advanced security systems for autonomous identification, assessment, and response to security threats in real-time. Recognising this challenge and the capabilities of NLP and AI approaches to fortify cyber security systems, the First International Conference on Natural Language Processing (NLP) and Artificial Intelligence (AI) for Cyber Security (NLPAICS’2024) offers to act as a meeting point for researchers working on NLP and AI methods for Cyber Security and welcomes contributions reporting latest solutions based on NLP and AI to mitigate the risks when processing digital information. Conference topics The conference invites submissions on a broad range of topics related to the employment of NLP and AI (and in general, language studies and models) for Cyber Security including but not limited to: Societal and Human Security and Safety * Content Legitimacy and Quality * Detection and mitigation of hate speech and offensive language * Fake news, deepfakes, misinformation and disinformation * Detection of machine generated language in multimodal context (text, speech and gesture) * User Security and Safety * Cyberbullying and identification of internet offenders * Monitoring extremist fora * Suicide prevention * Technical Measures and Solutions * Social engineering identification, phishing detection * NLP for risk assessment * Controlled languages for safe messages * Prevention of malicious use of ai models * Forensic linguistics * Human Factors in Cyber Security Speech Technology and Multimodal Investigations for Cyber Security * Voice-based security: Analysis of voice recordings or transcripts for security threats * Detection of machine generated language in multimodal context (text, speech and gesture) * NLP and biometrics in multimodal context Data and Software Security * Cryptography * Digital forensics * Malware detection, obfuscation * Models for documentation * NLP for data privacy and leakage prevention (DLP) * Addressing dataset “poisoning” attacks Human-Centric Security and Support * Natural language understanding for chatbots: NLP-powered chatbots for user support and security incident reporting * User behaviour analysis: Analysing user-generated text data (e.g., chat logs and emails) to detect insider threats or unusual behaviour * Human supervision of technology for Cyber Security Anomaly Detection and Threat Intelligence * Text-Based Anomaly Detection * Identification of unusual or suspicious patterns in logs, incident reports or other textual data * Detecting deviations from normal behaviour in system logs or network traffic * Threat Intelligence Analysis * Processing and analysing threat intelligence reports, news, articles and blogs on latest Cyber Security threats * Extracting key information and indicators of compromise (IoCs) from unstructured text Systems and Infrastructure Security * Systems Security * Anti-reverse engineering for protecting privacy and anonymity * Identification and mitigation of side-channel attacks * Authentication and access control * Enterprise-level mitigation * NLP for software vulnerability detection * Malware Detection through Code Analysis * Analysing code and scripts for malware * Detection using NLP to identify patterns indicative of malicious code Financial Cyber Security * Financial Fraud Detection * Algorithmic Trading Security * Secure Online Banking * Risk Management in Finance * Financial Text Analytics Ethics, Bias, and Legislation in Cyber Security * Ethical and Legal Issues * Digital privacy and identity management * The ethics of NLP and speech technology * Explainability of NLP and speech technology tools * Legislation against malicious use of AI * Regulatory issues * Bias and Security * Bias in Large Language Models (LLMs) * Bias in security related datasets and annotations Datasets and resources for Cyber Security Applications Specialised Security Applications and Open Topics * Intelligence applications * Emerging and innovative applications in Cyber Security Submissions and Publication The first call for papers (to be distributed in November 2023) will provide details on the types of submissions and the submission procedure. The first call will also provide information on the conference schedule, including submission and notification deadlines. Each submission will be reviewed by three members of the Programme Committee. All accepted papers will be included in the conference e-proceedings which will be available at the conference. The NLPAICS’2024 organisers will work with ACL to secure their inclusion in the ACL Anthology. Organisation The First International Conference on Natural Language Processing and Artificial Intelligence for Cyber Security (NLPAICS’2024) is organised by the Lancaster University UCREL NLP research group. Further information and contact details This is a first announcement only. The first Call for Papers is expected in November 2023 and registration will be open as from March 2024. The follow-up calls will list keynote speakers, conference chairs and members of the programme committee once confirmed. The conference website and the conference email address will be available soon. For any initial queries, please feel free to contact Prof Ruslan Mitkov on r.mitkov(a)lancaster.ac.uk.

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Re: [External] Re: NIF: NLP Interchange Format
by Bilgin, Orhan (Postgraduate Researcher) 18 Oct '23

18 Oct '23

I am sorry, I forgot to mention that the strings in my example are Turkish words, and the lemma AĞAÇ- corresponds to the lemma TREE- in English, which is a label that allows me to talk about the only meaningful thing that is common to the set {tree, trees}. Best, Orhan On 17 Oct 2023 20:44, "Bilgin, Orhan (Postgraduate Researcher)" <o.bilgin(a)lancaster.ac.uk> wrote: Dear Ada, I agree that lemmatisation is a construct and is not a universal method for linguistic analyses, but I don't understand why it is imperative that I wean myself from using lemmas. What is it that restricts my freedom to invent the lemma (a non-universal construct) AĞAÇ-, for example, to refer to the one and only "meaningful thing" that is common to the very many (theoretically infinite, practically probably around 10,000) strings including ağaç, ağacı, ağaca, ağaçlar, ağacımızdaki, ağaçlandırılabilmesinden, ağaçsızlaşmasını, etc. etc.? How (and why) am I supposed to talk about that very large set without using a label for it? Best, Orhan Bilgin On 17 Oct 2023 18:36, Ada Wan via Corpora <corpora(a)list.elra.info> wrote: This email originated outside the University. Check before clicking links or attachments. Dear Christian Re your PS: one doesn't need to debate the use/future of lemmatization, though I'd welcome such as part of scholarship. For those experienced in matters in/of Linguistics, it should be clear that lemmatization was simply a cconstruct, a entry-level philological exercise (esp. for those from Computer Science with less of a background in Linguistics and language(s)). It has been sad that some have picked up the habit of using lemmatization as a heuristic (though for what, specifically?) and might have become, apparently, too addicted to it to let it go. It is imperative that one weans themselves from such habit. Methods for linguistic morphology, e.g. (morphological) parsing or stemming, are not a universal decomposition scheme, nor a universal method for language/linguistic analyses. Also important is to bear in mind is that neither linguistic morphology nor lemmas/lemmata doesn't/don't have that long of a history. Thanks for being open-minded enough to read this far. Best Ada

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NIF: NLP Interchange Format
by Hugh Paterson III 17 Oct '23

17 Oct '23

Greetings, I am working on a project which is using lemmatization. I'm wondering how people have approached combining NIF and lemmatization. are there any "blessed" extensions or ontologies? I'm not seeing nif:lemma as an option within the nif ontology... though I am likely missing something. Kind regards, - Hugh

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Job Posting: Permanent Research Scientist and Assistant Professor positions in Nancy, France
by Slim Ouni 17 Oct '23

17 Oct '23

Job Posting: Permanent Research Scientist and Assistant Professor positions in Nancy, France The Multispeech team (https://team.inria.fr/multispeech <https://team.inria.fr/multispeech>) is seeking exceptional candidates for permanent (i.e., tenured) Research Scientist and Assistant Professor positions. A joint team of University of Lorraine, Inria, and CNRS, Multispeech focuses on spoken human-machine interaction, with particular attention to (1) data-efficient and privacy-preserving machine learning for speech processing, (2) information extraction from multimodal (i.e., acoustic, facial, articulatory, and gestural) speech, and (3) multimodal speech synthesis. We are currently expanding towards multimodal dialog, aiming to break the classical dialog management scheme to dynamically account for the user's behavior during the machine's response. Our research crystallizes into a software platform for the development of embodied voice assistants and aims to achieve concrete economic and social impact in the fields of healthcare and education. Situated at the heart of Europe, just 90 minutes from Paris and nestled between Germany, Belgium, and Luxembourg, Nancy is a city celebrated for its unique architectural style and gastronomy. Home to a vibrant student population of 50,000, the city offers many creative, cultural, sports, and outdoor activities. Notably, Nancy is recognized as one of the most affordable and environmentally friendly cities in France. If you're interested in joining us, please contact us as soon as possible. Candidates with expertise in natural language processing and dialog are particularly welcome. These positions are an excellent opportunity to work in a dynamic and collaborative environment where you will have the opportunity to make a significant contribution. Research Scientist positions do not involve teaching duties. Contact : Slim.Ouni(a)loria.fr <mailto:Slim.Ouni@loria.fr> <mailto:Slim.Ouni@loria.fr <mailto:Slim.Ouni@loria.fr>> Feel free to share this offer with anyone who might be interested.

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October 2023 Newsletter - LDC
by Penn LDC 16 Oct '23

16 Oct '23

In this newsletter: Membership Year 2024 publication preview Fall 2023 data scholarship recipients New publications: AIDA Scenario 1 Practice Topic Source Data<https://catalog.ldc.upenn.edu/LDC2023T11> AIDA Scenario 1 and 2 Reference Knowledge Base<https://catalog.ldc.upenn.edu/LDC2023T10> ________________________________ Membership Year 2024 publication preview The 2024 membership year is approaching and plans for next year's publications are in progress. Among the expected releases are: * KASET: 147 hours of Sorani Kurdish and Kurmanji Kurdish conversational telephone speech and web broadcasts, 65 hours transcribed * AIDA topic source data and annotations: multimodal source data and annotations in multiple languages (Russian, Ukrainian, English, Spanish) for information and entity extraction * RATS Low Speech Density Data: 87 hours of Levantine Arabic, English, Persian, Pushto, and Urdu audio files selected from RATS speech activity detection and keyword spotting data sets, also including communications systems sounds and silence * Call My Net 1: 364 hours of conversational telephone speech recordings in Tagalog, Cebuano, Cantonese, and Mandarin from speakers in the Philippines and China using various handsets under diverse noise conditions * Ravnursson Faroese Speech and Transcripts: 109 hours of read speech from 433 native speakers with transcripts * Diaspora Tibetan Speech: elicited, read, and spontaneous speech from 73 native Tibetan speakers in Katmandu's diaspora Tibetan community, some recordings transcribed * IARPA MATERIAL language packs: conversational telephone speech, transcripts, English translations, annotations, and queries in multiple languages (e.g., Bulgarian, Somali, Georgian) * LORELEI: representative and incident language packs containing monolingual text, bi-text, translations, annotations, supplemental resources, and related tools in various languages (e.g., Farsi, Hungarian, Hindi, Amharic) Check your inbox in the coming weeks for more information about membership renewal. Fall 2023 data scholarship recipients Congratulations to the recipients of LDC's Fall 2023 data scholarships: Nessma Diab: Ain-Shams University (Egypt): Pre-PhD student, Linguistics. Nessma is awarded copies of CALLHOME Egyptian Arabic Speech LDC97S45 and CALLHOME Egyptian Arabic Transcripts LDC97T10 for her work in machine translation. Soheir Elssakkout: Ain-Shams University (Egypt): PhD candidate. Soheir is awarded copies of Turkish Broadcast News and Transcripts LDC2012S06 and Middle East Technical University Turkish Microphone Speech v 1.0 LDC2006S33 for her work in speech recognition. Matheus Franco: Witten/Herdecke University (Germany): Post-doctoral scholar, Faculty of Management, Economics and Society. Matheus is awarded a copy of Avocado Research Email Collection LDC2015T03 for his work in emotional foundations of dynamic capabilities. Kamal Jarrar: Birzeit University (Palestine): Master's student, Applied Statistics and Data Science Program. Kamal is awarded copies of Arabic Gigaword Fifth Edition LDC2011T11 and BOLT Arabic Discussion Forums LDC2018T10 for his work in part-of-speech tagging for dialectal Arabic. Minkyoung Kim: Yonsei University (Korea); PhD candidate, Graduate School of Information. Minkyoung is awarded a copy of The New York Times Annotated Corpus LDC2018T19 for her work in event extraction and semantic event annotation. Humaira Mehmood: Fatima Jinnah Women University (Pakistan): Master's student, Computer Sciences. Humaira is awarded a copy of ARL Urdu Speech Database, Training Data LDC2007S03 for her work in machine translation. Diyam Mousa: Birzeit University (Palestine): PhD candidate, Computer Science Department. Diyam is awarded copies of Arabic Treebank: Part 3 v. 3.2 LDC2010T08 and BOLT Egyptian Arabic Treebank - Discussion Forum LDC2018T23 for her work in morphological tagging for dialectal Arabic. For information about the program, visit the Data Scholarships page<https://www.ldc.upenn.edu/language-resources/data/data-scholarships>. ________________________________ New publications: AIDA Scenario 1 Practice Topic Source Data<https://catalog.ldc.upenn.edu/LDC2023T11> was developed by LDC and is comprised of 1511 files (text, image, and video) from English, Russian, and Ukrainian web sources. Each phase of the AIDA program centered on a specific scenario, or broad topic area, with related subtopics designated as either practice subtopics or evaluation subtopics. The Phase 1 scenario focused on political relations between Russia and Ukraine in the 2010s. This corpus constitutes the full set of topic-focused documents for Phase 1 practice subtopics. Data was collected from web sources by a combination of automatic and manual processes. The DARPA AIDA (Active Interpretation of Disparate Alternatives) program aimed to develop a multi-hypothesis semantic engine to generate explicit alternative interpretations of events, situations, and trends from a variety of unstructured sources. LDC supported AIDA by collecting, creating and annotating multimodal linguistic resources in multiple languages. The knowledge base for entity detection and linking annotation for all AIDA Scenario 1 and 2 corpora is available separately as AIDA Scenario 1 and 2 Reference Knowledge Base (LDC2023T10)<https://catalog.ldc.upenn.edu/LDC2023T10>. 2023 members can access this corpus through their LDC accounts. Non-members may license this data for a fee. * AIDA Scenario 1 and 2 Reference Knowledge Base<https://catalog.ldc.upenn.edu/LDC2023T10> contains the English knowledge base (KB) used for all AIDA entity linking annotation in Scenario 1 (Russia-Ukraine Relations) and Scenario 2 (Crisis in Venezuela). The KB content was drawn from GeoNames, the CIA World Leaders List, and the CIA World Factbook and was supplemented with manually-created KB entries developed by LDC specifically for AIDA data. This knowledge base supported the AIDIA entity detection and linking task for 13 entity types: GPE (Geo-Political Entity), LOC (Location), PER (Person), ORG (Organization), FAC (Facility), MHI (Medical/Health Issue), WEA (Weapon), SID (Side), COM (Commodity), CRM (Crime), LAW (Law), VEH (Vehicle), and BAL (Ballot). 2023 members can access this corpus through their LDC accounts. Non-members may license this data for a fee. To unsubscribe from this newsletter, log in to your LDC account<https://catalog.ldc.upenn.edu/login> and uncheck the box next to "Receive Newsletter" under Account Options or contact LDC for assistance. Membership Coordinator Linguistic Data Consortium<ldc.upenn.edu> University of Pennsylvania T: +1-215-573-1275 E: ldc(a)ldc.upenn.edu<mailto:ldc@ldc.upenn.edu> M: 3600 Market St. Suite 810 Philadelphia, PA 19104

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PhD studentships in NLP, Speech Technology and Cognitive Science at the University of Edinburgh
by Alex Lascarides 16 Oct '23

16 Oct '23

PHD STUDENTSHIPS IN COMPUTATIONAL LINGUISTICS, SPEECH TECHNOLOGY AND COGNITIVE SCIENCE Institute for Language, Cognition and Computation School of Informatics University of Edinburgh The Institute for Language, Cognition and Computation (ILCC) at the University of Edinburgh invites applications for three-year PhD studentships starting in September 2024.. ILCC is dedicated to the pursuit of basic and applied research on computational approaches to language, communication and cognition. Primary research areas include: * Natural language processing and computational linguistics * Machine Translation * Speech technology * Dialogue, multimodal interaction, language and vision * Computational Cognitive Science , including language and speech, decision-making, learning and generalization * Social Media and Computational Social Science * Human-Computer interaction, design informatics, assistive and educational technology * Information retrieval and visualization Approximately 10 studentships from a variety of sources are available, covering both maintenance at the research council rate of GBP 19,162 (2024/25 rates) per year and tuition fees. Awards increase every year, typically with inflation. Studentships are available for UK, EU, and non-EU nationals. Applicants should have a strong undergraduate degree or equivalent in computer science, cognitive science, AI, or a related discipline. For a list of academic staff at ILCC with research areas, and for a list of indicative PhD topics, please consult: http://web.inf.ed.ac.uk/ilcc/people/academic-senior-research-staff http://www.ilcc.inf.ed.ac.uk/study/possible-phd-topics-in-ilcc Details regarding the PhD programme and the application procedure can be found at: http://www.ed.ac.uk/informatics/postgraduate/research-degrees/phd There are TWO DEADLINES for applications to receive full consideration: round 1: 24th November 2023 round 2: 26th January 2024 The link to the application portal is: https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/bySchoo… We strongly recommend that non-UK applicants submit their applications in round 1, to maximise their chances of funding. Please direct inquiries to the PhD admissions team at ilcc-admissions(a)inf.ed.ac.uk.

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CFP-The Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages -(DravidianLangTech-2024) at EACL 2024-reg
by Bharathi Raja Asoka Chakravarthi 14 Oct '23

14 Oct '23

Apologies for cross posting The Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages -(DravidianLangTech-2024) at EACL 2024 Link: https://sites.google.com/view/dravidianlangtech-2024/home The development of technology increases our internet use, and most of the global languages have adapted themselves to the digital era. However, there are many regional, under-resourced languages that face challenges as they still lack developments in language technology. One such language family is the Dravidian family of languages. Dravidian languages <https://en.wikipedia.org/wiki/Dravidian_languages> are primarily spoken in south India and Sri Lanka. Pockets of speakers are found in Nepal, Pakistan, Malaysia, other parts of India and elsewhere in the world. The Dravidian languages, which are 4,500 years old and spoken by millions of speakers, are under-resourced in speech and natural language processing. The Dravidian languages are divided into four groups: South, South-Central, Central, and North groups. Dravidian morphology is agglutinating and exclusively suffixal. Syntactically, Dravidian languages are head-final and left-branching. They are free-constituent order languages. To improve access to and production of information for monolingual speakers of Dravidian languages, it is necessary to have speech and language technologies. The aim of these workshops is to save the Dravidian languages from extinction in technology. This is the first workshop on speech and language technologies for Dravidian languages. The broader objectives of DravidianLangTech-2024 will be - To investigate challenges related to speech and language resource creation for Dravidian languages. - To promote research in speech and language technology in Dravidian languages. - To adopt appropriate language technology models which suit Dravidian languages. - To provide opportunities for researchers from the Dravidian language community from around the world to collaborate with other researchers. Our workshop theme focuses on being more inclusive and providing a platform for researchers to create Language Technologies (LT) of a more inclusive nature. We hope that through these engagements we can develop LT tools to be more inclusive of everyone, including marginalized people. Call for Papers DravidianLangTech-2024 welcomes theoretical and practical paper submission on any Dravidian languages (Tamil, Kannada, Malayalam, Telugu, Tulu, Allar, Aranadan, Attapadya, Kurumba, Badaga, Beary, Betta Kurumba, Bharia, Bishavan, Brahui, Chenchu, Duruwa, Eravallan, Gondi, Holiya, Irula, Jeseri, Kadar, Kaikadi, Kalanadi, Kanikkaran, Khiwar, Kodava, Kolami, Konda, Koraga, Kota, Koya, Kurambhag Paharia, Kui, Kumbaran, Kunduvadi, Kurichiya, Kurukh, Kurumba, Kuvi, Madiya, Mala Malasar, Malankuravan, Malapandaram, Malasar, Malto, Manda, Muduga, Mullu Kurumba, Muria, Muthuvan, Naiki, Ollari, Paliyan, Paniya, Pardhan, Pathiya, Pattapu, Pengo, Ravula, Sholaga, Thachanadan, Toda, Wayanad Chetti, and Yerukala) that contributes to research in language processing, speech technologies or resources for the same. We will particularly encourage studies that address either practical application or improving resources for a given language in the field. We invite submissions on topics that include, but are not limited to, the following: - Code-mixing/ Code-switching - Cognitive Modeling and Psycholinguistics - Computer-assisted language learning (CALL) - Corpus development, tools, analysis and evaluation - COVID-19 alert, NLP Applications for Emergency Situations and Crisis Management - Equality, Diversity, and Inclusion - Fake New, Spam, and Rumor Detection - Hate speech detection and Offensive Language Detection - Lexicons and Machine-readable dictionaries - Linguistic Theories, Phonology, Morphological analysis, Syntax and Semantics - Machine Translation, Sentiment Analysis, and Text summarization - Multimodal Analysis- Image Captioning and Video Captioning - Speech technology and Automatic Speech Recognition Important dates - Workshop paper due: *December 12, 2023* - Direct Submission deadline (pre-reviewed ARR & main conference): January 17, 2024 - Notification of acceptance: January 15, 2024 - Camera-ready papers due: January 25 2024 - Workshop dates: March 21-22, 2024 *Organizers* - Bharathi Raja Chakravarthi <https://www.universityofgalway.ie/our-research/people/computer-science/bhar…>, School of Computer Science, University of Galway, Ireland - Ruba Priyadharshini <https://scholar.google.co.in/citations?user=QD-mJd4AAAAJ&hl=en>, Gandhigram Rural Institute-Deemed to be University, India - Anand Kumar M <https://infotech.nitk.ac.in/faculty/anand-kumar-m>, Department of Information Technology, National Institute of Technology Karnataka Surathkal, India. - Sajeetha Thavareesan <https://fsc.esn.ac.lk/computing/academic-staff/s-thavareesan>, Department of Computing ,Faculty of Science, Eastern University, Sri Lanka. - Elizabeth Sherly <https://duk.ac.in/personnel/dr-elizabeth-sherly/>, Indian Institute of Information Technology and Management-Kerala, India. - Rajeswari Natarajan <https://www.sastra.edu/staffprofiles/schools/src.php?staff_id=C754>, Srinivasa Ramanujan Centre, Department of Computer Science, SASTRA University, India. - Manikandan Ravikiran <https://manikandan-ravikiran.github.io/>, Hitachi India Pvt Ltd. Submission Link: https://openreview.net/group?id=eacl.org/EACL/2024/Workshop/DravidianLangTe… with regards, Dr. Bharathi Raja Chakravarthi, Assistant Professor / Lecturer-above-the-bar School of Computer Science, University of Galway, Ireland Insight SFI Research Centre for Data Analytics, Data Science Institute, University of Galway, Ireland E-mail: bharathiraja.akr(a)gmail.com , bharathi.raja(a)universityofgalway.ie <bharathiraja.asokachakravarthi(a)universityofgalway.ie> Google Scholar: https://scholar.google.com/citations?user=irCl028AAAAJ&hl=en Website: https://www.universityofgalway.ie/our-research/people/bharathirajaasokachak…

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Re: NIF: NLP Interchange Format
by Hugh Paterson III 13 Oct '23

13 Oct '23

Hi Ada good to hear from you, The project is called: "The Bridge". https://bridge.haverford.edu/ I am not the PI. The project has been in existence for about 12 years. I was invited to become involved through my Drexel LEADING Fellowship. Here is a paper we published this summer: https://hughandbecky.us/Hugh-CV/publication/2023-bridging-corpora/4LR_pre_p… The Bridge is a linked data application supporting curriculum development. It was developed with Latin in mind, but has been extended to Greek as well. It quickly helps instructors and students find new vocabulary words in newly assigned texts, based on texts they have already encountered in their curriculum. The current workflow takes a variety of texts from several sources and then stores the lemmas for comparison across texts and broad stats generation. I see value in modeling the whole text not just the lemmas as this may allow future services. So, while NIF could model the whole text, the current operational activities really only involve using lemmas. To move forward in a linked data model we need to support current operations. More broadly, I see the lemmas as an "annotation" or abstraction layer whereas I would see the actual content of texts as the "source data". Using linked data and lemmas allows the bridge to connect via lemmas to LiLa data. https://lila-erc.eu/ Kind regards, Hugh On Tue, Oct 10, 2023 at 3:39 AM Ada Wan <adawan919(a)gmail.com> wrote: > Dear Hugh > > What project are you working on that still requires lemmatization? Would > it not be a better approach to use (sub-)character n-grams (esp. if you are > doing textual analysis/interpretation, vs. processing which can be > byte-based) to decipher what segments would occur most frequently first and > (re-)analyze from there? > I understand there has been a habit in the "language space" to call > certain segments "lemmata". I am curious to know what one can do as a > community, though, to transition to more general methods (and > interpretations on "language"). > > Thanks and best > Ada > > > On Tue, Oct 10, 2023 at 12:15 AM Hugh Paterson III via Corpora < > corpora(a)list.elra.info> wrote: > >> Greetings, >> >> I am working on a project which is using lemmatization. I'm wondering how >> people have approached combining NIF and lemmatization. are there any >> "blessed" extensions or ontologies? >> I'm not seeing nif:lemma as an option within the nif ontology... though I >> am likely missing something. >> >> Kind regards, >> - Hugh >> _______________________________________________ >> Corpora mailing list -- corpora(a)list.elra.info >> https://list.elra.info/mailman3/postorius/lists/corpora.list.elra.info/ >> To unsubscribe send an email to corpora-leave(a)list.elra.info >> >

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CFP-Fourth Workshop on Language Technology for Equality, Diversity, Inclusion (LT-EDI-2024) at EACL 2024-reg
by Bharathi Raja Asoka Chakravarthi 13 Oct '23

13 Oct '23

Apologies for cross posting *Fourth Workshop on Language Technology for Equality, Diversity, Inclusion (LT-EDI-2024) at EACL 2024* *Website link: https://sites.google.com/view/lt-edi-2024/ <https://sites.google.com/view/lt-edi-2024/> * Equality, Diversity and Inclusion (EDI) is an important agenda across every field throughout the world. Language as a major part of communication should be inclusive and treat everyone with equality. Today’s large internet community uses language technology (LT) and has a direct impact on people across the globe. EDI is crucial to ensure everyone is valued and included, so it is necessary to build LT that serves this purpose. Recent results have shown that big data and deep learning are entrenching existing biases and that some algorithms are even naturally biased due to problems such as ‘regression to the mode’. Our focus is on creating LT that will be more inclusive of gender, racial, sexual orientation, persons with disability. The workshop will focus on creating speech and language technology to address EDI not only in English, but also in less resourced languages. The broader objective of LT-EDI-2024 will be - To investigate challenges related to speech and language resource creation for EDI. - To promote research in inclusive LT. - To adopt and adapt appropriate LT models to suit EDI. - To provide opportunities for researchers from the LT community around the world to collaborate with other researchers to identify and propose possible solutions for the challenges of EDI. Our workshop theme focuses on being more inclusive and providing a platform for researchers to create LT of a more inclusive nature. We hope that through these engagements we can develop LT tools to be more inclusive of everyone, including marginalized people. *Call for Papers:* Our main theme in this workshop is equality, diversity, and inclusivity in LT. We invite researchers and practitioners to submit papers reporting on these issues and datasets to avoid these issues. We also encourage qualitative studies related to these issues and how to avoid them. LT-EDI-2024 welcomes theoretical and practical paper submissions on any languages that contribute to research in Equality, Diversity and Inclusion. We will particularly encourage studies that address either practical application or improving resources. *Topics of interest include, but are not limited to:* - Data set development to include EDI - Gender inclusivity in LT - LGBTQ+ inclusivity in LT - Racial inclusivity in LT - Persons with disability inclusivity in LT - Speech and language recognition for minority groups - Unconscious bias and how to avoid them in natural language processing, machine learning and other LT technologies. - Tackling rumours and fake news about gender, racial, and LGBTQ+ minorities. - Tackling discrimination against gender, racial, and LGBTQ+ minorities. Submissions: At LTEDI we accept the following submission types: - Long paper submissions must describe substantial, original, completed and unpublished work. Wherever appropriate, concrete evaluation and analysis should be included. Long papers may consist of up to 8 pages of content, plus unlimited pages for references and appendices. Upon acceptance, long papers will be given one additional page of content (i.e. up to 9 pages) in the proceedings so that reviewers’ comments can be taken into account. - Short paper submissions must describe original and unpublished work. Please note that a short paper is not a shortened long paper. Instead, short papers should have a point that can be made in a few pages. Short papers may consist of up to 4 pages of content, plus unlimited references and appendices. Upon acceptance, short papers will be given one additional page of content (i.e. up to 5 pages) in the proceedings so that reviewers’ comments can be taken into account. - Poster and demo submissions should be no longer than 4 pages (plus unlimited number of pages for references and ethics/broader impact statement). More information on submission can be found at https://sites.google.com/view/lt-edi-2024/submission For electronic submission of all papers, please use: https://openreview.net/group?id=eacl.org/EACL/2024/Workshop/LTEDI *Important Dates* - Workshop paper due: December 12, 2023 - Direct Submission deadline (pre-reviewed ARR & main conference) January 17, 2024 - Notification of acceptance: January 15, 2024 - Camera-ready papers due: January 25 2024 - Workshop dates: March 21-22, 2024 with regards, Dr. Bharathi Raja Chakravarthi, Assistant Professor / Lecturer-above-the-bar School of Computer Science, University of Galway, Ireland Insight SFI Research Centre for Data Analytics, Data Science Institute, University of Galway, Ireland E-mail: bharathiraja.akr(a)gmail.com , bharathi.raja(a)universityofgalway.ie <bharathiraja.asokachakravarthi(a)universityofgalway.ie> Google Scholar: https://scholar.google.com/citations?user=irCl028AAAAJ&hl=en Website: https://www.universityofgalway.ie/our-research/people/bharathirajaasokachak…

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[Open Position] Research Engineer - Machine Learning and Large Language Models - EURECOM
by Raphaël Troncy 13 Oct '23

13 Oct '23

[Apologies for Cross-Posting] The Data Science Department at EURECOM, Sophia-Antipolis France, invites applications for a Research Engineer position. The candidate will work as part of a department-wide project, which aims at developing our research activities on large language models (LLMs). We are looking for fresh, ambitious and hard-working software engineers with a clear passion for turning ideas in the field of machine learning into fully-functional prototypes, demonstrators, and systems, using cutting edge machine learning libraries, and computing facilities. The position is funded by a French National project on Artificial Intelligence, and targets the development of LLMs in several flavors. Our first goal is to target an audience of EURECOM staff, including researchers and administration, to offer novel conversational agents that can use internal, multimodal information to interact with users for Q&A, summarization, in-filling and many other tasks. A second ambitious goal is to offer innovative educational services to EURECOM students, by designing novel conversational agents instructed to follow Socratic interactions. Such conversational agents will be augmented with teaching material (lecture notes, slides, video lectures, code from labs, etc…) which should be used and referenced in conversations. The successful candidate will work in close relation with professors, postdoctoral researchers and Ph.D. candidates, and will lead contributions to: (i) the implementation and deployment of state-of-the art, open-source LLMs, including inner components (novel attention mechanisms, novel tokenization schemes, key-value caching, to name a few) and outer components (such as retrieval augmented generation) (ii) the definition of appropriate methodologies for training and, most importantly, fine-tuning of our internal LLMs, (iii) the definition of appropriate benchmarks and validation methodologies, and (iv) communication to a public of developers, engineers and practitioners through technical blogs, online demonstrators (e.g. HuggingFace spaces, on-site deployment) of our results, as well as to demonstrate the various releases of the prototype to EURECOM management teams. Since our activities are fueled by an important public fund, in the context of the French Government plan for AI, called the 3IA, the successful candidate will also participate to project meetings and reviews, as well as public demonstrations of research results. Requirements: * Education Level / Degree: Ms.c. or Ph.D. degree in Computer Science, Applied Mathematics, Physics, or a closely related area with a strong background on algorithmic development and software engineering * Applicants should have a good background on machine learning, a taste for learning new topics related to machine learning research, as well as proven experience in the design of solid software engineering artifacts * Applicants should have strong communication skills, with target audiences ranging from the scientific and academic community, as well as engineers and product managers * The working language in the department is English. Application The application must include: * Detailed curriculum, including (if available) a list of software engineering projects, public demonstrators, and contributions to open-source projects * a cover letter describing the applicant’s interests the contact details of 2/3 persons that can provide references about the candidate * the transcripts of courses taken at graduate (and optionally undergraduate) level Applications should be submitted by e-mail to Pietro.Michiardi(a)eurecom.fr and secretariat(a)eurecom.fr with the reference : DS/PM/EFELIA-LLM/102023 Applications will be accepted until the position is filled. Start date: ASAP -- Raphaël Troncy EURECOM, Campus SophiaTech Data Science Department 450 route des Chappes, 06410 Biot, France. e-mail: raphael.troncy(a)eurecom.fr & raphael.troncy(a)gmail.com Tel: +33 (0)4 - 9300 8242 Fax: +33 (0)4 - 9000 8200 Web: http://www.eurecom.fr/~troncy/

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