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20242026
most citedMedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding

3 citations · 7 across the 22 of their papers we have counts for

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9 papers · 1 filter

cs.AI2026

Dual Exam: Controlled Evaluation of Multimodal Agents and World Models

Zhefan Rao, Meng Chu, Xuan Zhang +80

World Models (WMs) can support Multimodal Agents (MAs) through simulated experience, while Agent trajectories can inform World Model refinement. Evaluating this interaction require…

cs.AI2026

AutoSFT: An Agentic System for Automated Data Research in Supervised Fine-Tuning

Bingxiang He, Pengqi Sun, Shihao Peng +18

Language model agents increasingly automate post-training, but when given the full training stack they converge on supervised fine-tuning and spend most effort revising training da…

cs.AI2026

StudyBench: Can Self-Evolution Squeeze Textbooks for Olympiad Capability?

Yinghao Chen, Zixi Chen, Bingxiang He +7

Humans need to study only a handful of well-written textbooks to master a discipline and attempt its hardest problems. We argue that an ideal self-evolution method should share the…

cs.AI2026

Rethinking On-Policy Distillation of Large Language Models II: One Training Example

Zixuan Fu, Bingxiang He, Yuxin Zuo +10

On-policy distillation (OPD) combines student-generated rollouts with dense token-level supervision from a teacher. Existing work has mainly studied its algorithmic behavior, leavi…

cs.AI2026

Towards Knowledgeable Deep Research: Framework and Benchmark

Wenxuan Liu, Zixuan Li, Long Bai +13

Deep Research (DR) requires LLM agents to autonomously perform multi-step information seeking, processing, and reasoning to generate comprehensive reports. In contrast to existing…

cs.AI2026

P1-VL: Bridging Visual Perception and Scientific Reasoning in Physics Olympiads

Yun Luo, Futing Wang, Qianjia Cheng +28

The transition from symbolic manipulation to science-grade reasoning represents a pivotal frontier for Large Language Models (LLMs), with physics serving as the critical test ancho…

cs.AI2025

Automating Exploratory Multiomics Research via Language Models

Shang Qu, Ning Ding, Linhai Xie +13

This paper introduces PROTEUS, a fully automated system that produces data-driven hypotheses from raw data files. We apply PROTEUS to clinical proteogenomics, a field where effecti…

cs.AI2025★ 3 cited

MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding

Yuxin Zuo, Shang Qu, Yifei Li +6

We introduce MedXpertQA, a highly challenging and comprehensive benchmark to evaluate expert-level medical knowledge and advanced reasoning. MedXpertQA includes 4,460 questions spa…

cs.AI2024

Automating Exploratory Proteomics Research via Language Models

Ning Ding, Shang Qu, Linhai Xie +13

With the development of artificial intelligence, its contribution to science is evolving from simulating a complex problem to automating entire research processes and producing nov…