6 citations · 17 across the 32 of their papers we have counts for
5 papers · 2 filters
Decomposition-Enhanced Training for Post-Hoc Attributions In Language Models
Sriram Balasubramanian, Samyadeep Basu, Koustava Goswami +6
Large language models (LLMs) are increasingly used for long-document question answering, where reliable attribution to sources is critical for trust. Existing post-hoc attribution…
Hop, Skip, and Overthink: Diagnosing Why Reasoning Models Fumble during Multi-Hop Analysis
Anushka Yadav, Isha Nalawade, Srujana Pillarichety +7
The emergence of reasoning models and their integration into practical AI chat bots has led to breakthroughs in solving advanced math, deep search, and extractive question answerin…
A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations
Li Li, Peilin Cai, Ryan A. Rossi +21
We present PersonaConvBench, a large-scale benchmark for evaluating personalized reasoning and generation in multi-turn conversations with large language models (LLMs). Unlike exis…
A Closer Look at Bias and Chain-of-Thought Faithfulness of Large (Vision) Language Models
Sriram Balasubramanian, Samyadeep Basu, Soheil Feizi
Chain-of-thought (CoT) reasoning enhances performance of large language models, but questions remain about whether these reasoning traces faithfully reflect the internal processes…
On Mechanistic Circuits for Extractive Question-Answering
Samyadeep Basu, Vlad Morariu, Zichao Wang +4
Large language models are increasingly used to process documents and facilitate question-answering on them. In our paper, we extract mechanistic circuits for this real-world langua…