Lab. for Computational Social Systems, a group led by @Tanmoy_Chak working on #SocialComputing #GraphMining & #NLProc
New Delhi, India
Joined July 2018
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🚀 #EMNLPFindings2026 #SneakPeek 🚀
Can we uncover the hidden limitations of scientific papers that reviews may overlook? Tree-of-Concerns introduces a multi-agent framework for extracting unstated limitations through structured critique.
📜 aclanthology.org/2026.findin…
We introduce ToC-Bench, a benchmark containing 414 research papers and 1,905 unstated limitations.
Tree-of-Concerns achieves:
✅ 79% higher precision
✅ 11% higher coverage
On the held-out evaluation, it achieves 40.3% precision and 36.1% Coverage@10.
The takeaway: effective scientific critique requires more than multiple AI opinions. It needs diverse perspectives, adversarial scrutiny, and careful reconciliation. #NLProc #MultiAgentSystems #LLMs #PeerReview #AIforScience
📰 Media Feature Alert 📢
Glad to see our perspectives on efficient AI and Small Language Models featured in Lokmat Times! The future of AI is not just about building larger models, but about making them smaller, more efficient, and accessible. @Tanmoy_Chak
#EfficientAI #SLMs
🚀 #EMNLP2026 #SneakPeek 🚀 Do multilingual LLMs understand diverse cultures, or do they still favor Western-associated entities? We introduce Camellia, a benchmark for measuring cultural biases across Asian languages and cultures. 🌏
🔗 Paper: aclanthology.org/2026.emnlp-…
⚠️ Language matters: Entity extraction gaps across cultures can reach 12–20% in Asian languages, substantially exceeding those generally observed in English.
🔬 The takeaway: Multilingual capability does not automatically translate into cultural understanding.
Camellia offers a systematic way to measure cultural biases and advance more culturally aware, equitable multilingual LLMs.
#EMNLP2026 #NLProc #ResponsibleAI #MultilingualAI
🚀 #EMNLP2026 #SneakPeek 🚀
Excited to share our work on a key challenge in #MentalHealthAI: How can we generate realistic, clinically grounded counseling dialogues when real therapy data is scarce due to privacy and ethical constraints?
ukplab.github.io/emnlp2026-g…
🧵👇
📊 Graph2Counsel generates 760 synthetic counseling sessions from 76 CPGs.
🏆 Expert evaluation ranks it highest among the compared datasets for specificity, counselor competence, authenticity, conversational flow, and safety, with strong inter-annotator agreement.
🔬 We also introduce Therapy-Eval, a framework for evaluating models through multi-turn simulated counseling conversations. Fine-tuning on Graph2Counsel improves several counseling metrics.
💻 Code: github.com/UKPLab/emnlp2026-…
#NLP #MentalHealthAI #ResponsibleAI #EMNLP2026
