*Homophobia and Transphobia Meme Classification | LT-EDI @ ACL 2026* We are pleased to invite the research community to participate in the LT-EDI @ ACL 2026 shared task on Homophobia and Transphobia Meme Classification, which addresses harmful multimodal content targeting LGBTQ+ individuals and communities.

Memes function as compact multimodal communication units that combine visual and textual cues. They spread rapidly across cultures and languages. This combination enables both subtle and explicit forms of discrimination. The shared task focuses on the automatic identification of homophobic and transphobic content in memes.

* 📝 Task Description*The shared task focuses on multiclass meme classification for detecting anti-LGBT content. Participants are provided with multimodal memes and are required to classify each meme into one of the predefined categories based on the presence of discriminatory content.

*Labels:*Homophobia Transphobia Non-anti-LGBT

*Languages:*English, Hindi, and Chinese

*Description:*Separate datasets are released for each language, enabling analysis across culturally distinct meme collections. The task requires participants to identify discriminatory stereotypes, harmful visual elements, and derogatory textual cues embedded in memes. All training and test datasets are developed following culturally sensitive and ethical annotation practices. The task emphasizes robust multimodal understanding across diverse cultural contexts.

* 📚 Resources* 🔗 Competition link (Codabench): https://www.codabench.org/competitions/11335/ 🔗 Task website: https://sites.google.com/view/lt-edi-2026/shared-tasks

*🗓️ Important Dates*Task announcement: November 16, 2025 Training data release: November 25, 2025 Test data release: January 20, 2026 Run submission deadline: February 10, 2026 Results announcement: February 16, 2026 Paper submission deadline: March 5, 2026 Peer review notification: April 28, 2026 Camera-ready submission: May 12, 2026 Workshop dates: July 2–3, 2026

with regards, Dr. Bharathi Raja Chakravarthi, Assistant Professor / Lecturer-above-the-bar Programme Director (MSc Computer Science - Artificial Intelligence) https://www.universityofgalway.ie/courses/taught-postgraduate-courses/computer-science-artificial-intelligence.html 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@gmail.com , bharathi.raja@universityofgalway.ie bharathiraja.asokachakravarthi@universityofgalway.ie Google Scholar: https://scholar.google.com/citations?user=irCl028AAAAJ&hl=en Website: https://research.universityofgalway.ie/en/persons/bharathi-raja-asoka-chakra...