16 citations · 27 across the 21 of their papers we have counts for
10 papers · 1 filter
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…
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,…
: A Simple Society of Language Models Solves Complex Reasoning
Gurusha Juneja, Subhabrata Dutta, Tanmoy Chakraborty
Despite demonstrating emergent reasoning abilities, Large Language Models (LLMS) often lose track of complex, multi-step reasoning. Existing studies show that providing guidance vi…
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…
Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoning
Gurusha Juneja, Subhabrata Dutta, Soumen Chakrabarti +2
Large Language Models (LLMs) prompted to generate chain-of-thought (CoT) exhibit impressive reasoning capabilities. Recent attempts at prompt decomposition toward solving complex,…
Multilingual LLMs are Better Cross-lingual In-context Learners with Alignment
Eshaan Tanwar, Subhabrata Dutta, Manish Borthakur +1
In-context learning (ICL) unfolds as large language models become capable of inferring test labels conditioned on a few labeled samples without any gradient update. ICL-enabled lar…
Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?
Subhabrata Dutta, Jeevesh Juneja, Dipankar Das +1
Identifying argument components from unstructured texts and predicting the relationships expressed among them are two primary steps of argument mining. The intrinsic complexity of…
How did the discussion go: Discourse act classification in social media conversations
Subhabrata Dutta, Tanmoy Chakraborty, Dipankar Das
We propose a novel attention based hierarchical LSTM model to classify discourse act sequences in social media conversations, aimed at mining data from online discussion using text…