6 papers
Co-FactChecker: A Framework for Human-AI Collaborative Claim Verification Using Large Reasoning Models
Dhruv Sahnan, Subhabrata Dutta, Tanmoy Chakraborty +2
Professional fact-checkers rely on domain knowledge and deep contextual understanding to verify claims. Large language models (LLMs) and large reasoning models (LRMs) lack such gro…
Mechanistic Behavior Editing of Language Models
Joykirat Singh, Subhabrata Dutta, Tanmoy Chakraborty
Large Language Models trained on web-scale text acquire language generation abilities that can solve a wide range of tasks, particularly when task knowledge is refined into the gen…
Can LLMs replace Neil deGrasse Tyson? Evaluating the Reliability of LLMs as Science Communicators
Prasoon Bajpai, Niladri Chatterjee, Subhabrata Dutta +1
Large Language Models (LLMs) and AI assistants driven by these models are experiencing exponential growth in usage among both expert and amateur users. In this work, we focus on ev…
Self-similarity of temporal interaction networks arises from hyperbolic geometry with time-varying curvature
Subhabrata Dutta, Dipankar Das, Tanmoy Chakraborty
The self-similarity of complex systems has been studied intensely across different domains due to its potential applications in system modeling, complexity analysis, etc., as well…
Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Tasks
Anwoy Chatterjee, Eshaan Tanwar, Subhabrata Dutta +1
Large Language Models (LLMs) have transformed NLP with their remarkable In-context Learning (ICL) capabilities. Automated assistants based on LLMs are gaining popularity; however,…
How to think step-by-step: A mechanistic understanding of chain-of-thought reasoning
Subhabrata Dutta, Joykirat Singh, Soumen Chakrabarti +1
Despite superior reasoning prowess demonstrated by Large Language Models (LLMs) with Chain-of-Thought (CoT) prompting, a lack of understanding prevails around the internal mechanis…