Publications

Mod-Guide: An LLM-based Content Moderation Feedback System to Address Insensitive Speech toward Indigenous Ethnic and Religious Minority Communities

ACM COMPASS 2026 (Accepted)

Co-created a culturally grounded corpus of insensitive speech with members of Bangladesh’s Hindu and Chakma communities; integrated those narratives into LLM moderation via RAG. Mixed-method evaluation shows RAG-enhanced moderation is more contextually accurate and perceived differently across ethnic lines.

Dipto Das, Achhiya Sultana, Ankit Singh Chauhan, Saadia Binte Alam, Mohammad Shidujaman, Sunandan Chakraborty, and Syed Ishtiaque Ahmed. (2026). "Can LLM-based Content Moderation Identify Insensitive Speech toward Indigenous Ethnic and Religious Minorities?" ACM COMPASS 2026. (Accepted)
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Benchmarking LLMs for Pairwise Causal Discovery in Biomedical and Multi-Domain Contexts

IEEE International Conference on Big Data

Benchmark of 13 open-source LLMs on pairwise causal discovery across 12 datasets — covers both detection and span-level extraction under zero-shot, CoT, and few-shot ICL. Best detection model scores 49.57% (Cdetect); performance collapses on implicit and multi-sentence cases.

Sydney Anuyah, Sneha Shajee Mohan, Bofu Dong, Ankit Singh Chauhan, Sunandan Chakraborty. (2025). "Examining Pairwise Causal Discovery in open-source Large Language Models using Prompt Tuning. " 2025 IEEE International Conference on Big Data. (To appear)
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