3 papers
cs.IR2026
CMASS: A ClimbMix Agentic Search Suite for Evaluating Search Agents Across Heterogeneous Tasks
Sahel Sharifymoghaddam, Lingwei Gu, Yijun Ge +1
Evaluating advances in agentic search requires testing whether methods generalize across tasks and corpus scale. Changing web search services impede controlled comparisons, while s…
cs.CL2026
NanoKnow: How to Know What Your Language Model Knows
Lingwei Gu, Nour Jedidi, Jimmy Lin
How do large language models (LLMs) know what they know? Answering this question has been difficult because pre-training data is often a "black box" - unknown or inaccessible. The…
cs.CV2024
NoisyEQA: Benchmarking Embodied Question Answering Against Noisy Queries
Tao Wu, Chuhao Zhou, Yen Heng Wong +2
The rapid advancement of Vision-Language Models (VLMs) has significantly advanced the development of Embodied Question Answering (EQA), enhancing agents' abilities in language unde…