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20202026
most citedFaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"

3 citations · 9 across the 11 of their papers we have counts for

collaborators
Showing 2025Show all

6 papers · 1 filter

cs.CL2025

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…

cs.AI2025

Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math

Shrey Pandit, Austin Xu, Xuan-Phi Nguyen +3

Large language model (LLM)-based reasoning systems have recently achieved gold medal-level performance in the IMO 2025 competition, writing mathematical proofs where, to receive fu…

cs.AI2025

SFR-DeepResearch: Towards Effective Reinforcement Learning for Autonomously Reasoning Single Agents

Xuan-Phi Nguyen, Shrey Pandit, Revanth Gangi Reddy +4

Equipping large language models (LLMs) with complex, interleaved reasoning and tool-use capabilities has become a key focus in agentic AI research, especially with recent advances…

cs.CV2025

EgoVLM: Policy Optimization for Egocentric Video Understanding

Ashwin Vinod, Shrey Pandit, Aditya Vavre +1

Emerging embodied AI applications, such as wearable cameras and autonomous agents, have underscored the need for robust reasoning from first person video streams. We introduce EgoV…

cs.CL2025

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…

cs.CL2025★ 2 cited

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…