3 citations · 4 across the 4 of their papers we have counts for
7 papers
iSight: Towards expert-AI co-assessment for improved immunohistochemistry staining interpretation
Jacob S. Leiby, Jialu Yao, Pan Lu +17
Immunohistochemistry (IHC) provides information on protein expression in tissue sections and is commonly used to support pathology diagnosis and disease triage. While AI models for…
TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular Reasoning
Jiaru Zou, Soumya Roy, Vinay Kumar Verma +6
Process Reward Models (PRMs) have recently emerged as a powerful framework for enhancing the reasoning capabilities of large reasoning models (LRMs), particularly in the context of…
Learning Human-Perceived Fakeness in AI-Generated Videos via Multimodal LLMs
Xingyu Fu, Siyi Liu, Yinuo Xu +13
Can humans identify AI-generated (fake) videos and provide grounded reasons? While video generation models have advanced rapidly, a critical dimension -- whether humans can detect…
Where LLM Agents Fail and How They can Learn From Failures
Kunlun Zhu, Zijia Liu, Bingxuan Li +15
Large Language Model (LLM) agents, which integrate planning, memory, reflection, and tool-use modules, have shown promise in solving complex, multi-step tasks. Yet their sophistica…
Fractional Reasoning via Latent Steering Vectors Improves Inference Time Compute
Sheng Liu, Tianlang Chen, Pan Lu +4
Test-time compute has emerged as a powerful paradigm for improving the performance of large language models (LLMs), where generating multiple outputs or refining individual chains…
Solving Inequality Proofs with Large Language Models
Pan Lu, Jiayi Sheng, Luna Lyu +4
Inequality proving, crucial across diverse scientific and mathematical fields, tests advanced reasoning skills such as discovering tight bounds and strategic theorem application. T…