From the 1 of 11 linked papers with an AI index.
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MultAttnAttrib: Training-Free Multimodal Attribution in Long Document Question Answering
Dang Quang Thien Tran, Quang V. Dang, Vinamra Tyagi +7
As grounded QA systems are increasingly deployed in AI assistants, accurately attributing generated answers to evidence is critical for user trust and model safety. While unimodal…
Spinning Straw into Gold: Relabeling LLM Agent Trajectories in Hindsight for Successful Demonstrations
Zichao Li, Gang Wu, Zichao Wang +5
Large language model agents operate in partially observable, long-horizon settings where obtaining supervision remains a major bottleneck. We address this by utilizing a source of…
Reasoning-Based Personalized Generation for Users with Sparse Data
Bo Ni, Branislav Kveton, Samyadeep Basu +14
Large Language Model (LLM) personalization holds great promise for tailoring responses by leveraging personal context and history. However, real-world users usually possess sparse…
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…
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…
Persona-SQ: A Personalized Suggested Question Generation Framework For Real-world Documents
Zihao Lin, Zichao Wang, Yuanting Pan +5
Suggested questions (SQs) provide an effective initial interface for users to engage with their documents in AI-powered reading applications. In practical reading sessions, users h…