most citedSuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

4 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026

AHEAD: Adaptive Hindsight with Environment-Augmented Distillation for Agentic RL

Xiaolong Jin, Dingmin Wang, Vijay Lingam +1

Training multi-turn LLM agents with reinforcement learning typically relies on trajectory-level rewards, which assign a uniform advantage to every step and cannot identify which de…

cs.CL2026

OpenClaw-RL: Train Any Agent Simply by Talking

Yinjie Wang, Xuyang Chen, Xiaolong Jin +2

Every agent interaction generates a next-state signal, namely the user reply, tool output, terminal or GUI state change that follows each action, yet no existing agentic RL system…

cs.SE2025

BigCodeArena: Unveiling More Reliable Human Preferences in Code Generation via Execution

Terry Yue Zhuo, Xiaolong Jin, Hange Liu +37

Crowdsourced model evaluation platforms, such as Chatbot Arena, enable real-time evaluation from human perspectives to assess the quality of model responses. In the coding domain,…

cs.CR2025

An Investigation on Group Query Hallucination Attacks

Kehao Miao, Xiaolong Jin

With the widespread use of large language models (LLMs), understanding their potential failure modes during user interactions is essential. In practice, users often pose multiple q…

cs.AI2025

SkillWeaver: Web Agents can Self-Improve by Discovering and Honing Skills

Boyuan Zheng, Michael Y. Fatemi, Xiaolong Jin +8

To survive and thrive in complex environments, humans have evolved sophisticated self-improvement mechanisms through environment exploration, hierarchical abstraction of experience…

cs.CL2025★ 4 cited

SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

P Team, Xinrun Du, Yifan Yao +94

Large language models (LLMs) have demonstrated remarkable proficiency in mainstream academic disciplines such as mathematics, physics, and computer science. However, human knowledg…