2 citations · 4 across the 9 of their papers we have counts for
6 papers · 1 filter
Synthesizing Agentic Data for Web Agents with Progressive Difficulty Enhancement Mechanisms
Shrey Pandit, Xuan-Phi Nguyen, Yifei Ming +4
Web-based 'deep research' agents aim to solve complex question - answering tasks through long-horizon interactions with online tools. These tasks remain challenging, as the underly…
Teaching with Lies: Curriculum DPO on Synthetic Negatives for Hallucination Detection
Shrey Pandit, Ashwin Vinod, Liu Leqi +1
Aligning large language models (LLMs) to accurately detect hallucinations remains a significant challenge due to the sophisticated nature of hallucinated text. Recognizing that hal…
MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models
Shrey Pandit, Jiawei Xu, Junyuan Hong +4
Advancements in Large Language Models (LLMs) and their increasing use in medical question-answering necessitate rigorous evaluation of their reliability. A critical challenge lies…
FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"
Yifei Ming, Senthil Purushwalkam, Shrey Pandit +4
Ensuring faithfulness to context in large language models (LLMs) and retrieval-augmented generation (RAG) systems is crucial for reliable deployment in real-world applications, as…
SFR-RAG: Towards Contextually Faithful LLMs
Xuan-Phi Nguyen, Shrey Pandit, Senthil Purushwalkam +7
Retrieval Augmented Generation (RAG), a paradigm that integrates external contextual information with large language models (LLMs) to enhance factual accuracy and relevance, has em…
CodeUpdateArena: Benchmarking Knowledge Editing on API Updates
Zeyu Leo Liu, Shrey Pandit, Xi Ye +2
Large language models (LLMs) are increasingly being used to synthesize and reason about source code. However, the static nature of these models' knowledge does not reflect the fact…