most citedOpenNovelty: An LLM-powered Agentic System for Verifiable Scholarly Novelty Assessment

4 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Atria Dawn: The Dawn of Agentic Superintelligence

Honglin Guo, Tao Gui, Yicheng Chen +139

As AI agents become participants in the development of their successors, they reshape both the production of intelligence and the role of human researchers. We introduce Atria Dawn…

cs.CL2026

SciAgentGym: Benchmarking Multi-Step Scientific Tool-use in LLM Agents

Yujiong Shen, Yajie Yang, Zhiheng Xi +17

Scientific reasoning inherently demands integrating sophisticated toolkits to navigate domain-specific knowledge. Yet, current benchmarks largely overlook agents' ability to orches…

cs.IR2026★ 4 cited

OpenNovelty: An LLM-powered Agentic System for Verifiable Scholarly Novelty Assessment

Ming Zhang, Kexin Tan, Yueyuan Huang +20

Evaluating novelty is critical yet challenging in peer review, as reviewers must assess submissions against a vast, rapidly evolving literature. This report presents OpenNovelty, a…

cs.CL2025

LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models

Ming Zhang, Yujiong Shen, Jingyi Deng +19

Existing evaluation of Large Language Models (LLMs) on static benchmarks is vulnerable to data contamination and leaderboard overfitting, critical issues that obscure true model ca…

cs.CL2025★ 1 cited

LLMEval-Med: A Real-world Clinical Benchmark for Medical LLMs with Physician Validation

Ming Zhang, Yujiong Shen, Zelin Li +13

Evaluating large language models (LLMs) in medicine is crucial because medical applications require high accuracy with little room for error. Current medical benchmarks have three…