collaborators

10 papers

cs.AI2026

REVEAL: Reverse Engineering Agentic Latents from Frontier-Model Traces

Yuetian Du, Meng Wang, Yucheng Wang +9

Frontier LLM agents perform complex interactive tasks, but their inference costs motivate transferring their experience to smaller open-source agents. Distillation and latent commu…

cs.AI2026

Science Edge Evaluation: SEE the Missing Step Toward Real Scientific Discovery

Taolin Han, Yuchen Zhang, Jinghang Wang +22

Large language models (LLMs) are increasingly involved in scientific discovery, yet it remains unclear whether they can support complex real laboratory science. Here we introduce S…

cs.AI2026

Right Answer, Wrong Method: Shortcut Hacking Misleads the Evaluation of LLM Reasoning on Frontier Science Benchmarks

Xuan Ren, Weiqi Zhai, Tianle Pu +3

Scientific reasoning benchmarks typically evaluate large language models (LLMs) using final-answer accuracy. However, a correct answer does not necessarily demonstrate the reasonin…

cs.CL2026

Before the Action: Benchmarking LLMs on Prospective Hypothesis Discovery

Tianyun Zhong, Wangyi Jiang, Wei Wang +15

Large language models (LLMs) excel at answering pre-specified questions, yet their ability to navigate the open-ended, pre-conclusion stage of discovery remains largely unmeasured.…

cs.AI2026

LongMedBench: Benchmarking Medical Agents for Long-Horizon Clinical Decision-Making

Zihan Xu, Yanzhen Chen, Xiaocheng Zhang +4

In this work, we introduce LongMedBench, a real-world EHR-based benchmark for long-horizon clinical decision-making. Prior evaluations of LLM-based medical agents have largely emph…

cs.CL2026

MedPRMBench: A Fine-grained Benchmark for Process Reward Models in Medical Reasoning

Lingyan Wu, Xiang Zheng, Weiqi Zhai +5

Medical reasoning can reach a plausible answer while overlooking an unsafe or unsupported intermediate step. Process-Level Reward Models (PRMs) can verify such steps, yet existing…

cs.CL2026

ClinConsensus: A Physician-Calibrated Benchmark for Evaluating Clinical Rubric Coverage in Chinese Medical LLMs

Xiang Zheng, Han Li, Wenjie Luo +15

Open-ended medical LLM evaluation remains weakly grounded in physician-calibrated coverage of clinically relevant response criteria, especially in localized clinical settings. We i…

cs.AI2026

Unmasking Reasoning Processes: A Process-aware Benchmark for Evaluating Structural Mathematical Reasoning in LLMs

Xiang Zheng, Weiqi Zhai, Wei Wang +15

Recent large language models (LLMs) achieve near-saturation accuracy on many established mathematical reasoning benchmarks, raising concerns about their ability to diagnose genuine…

cs.CL2026

HLE-Verified: A Systematic Verification and Structured Revision of Humanity's Last Exam

Weiqi Zhai, Zhihai Wang, Jinghang Wang +33

Humanity's Last Exam (HLE) has become a widely used benchmark for evaluating frontier large language models on challenging, multi-domain questions. However, community-led analyses…

cs.CL2025

SKYLENAGE Technical Report: Mathematical Reasoning and Contest-Innovation Benchmarks for Multi-Level Math Evaluation

Hu Wei, Ze Xu, Boyu Yang +15

Large language models (LLMs) now perform strongly on many public math suites, yet frontier separation within mathematics increasingly suffers from ceiling effects. We present two c…