most citedAre We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer Review

9 citations · 12 across the 3 of their papers we have counts for

collaborators

6 papers

cs.AI2025

BrowseMaster: Towards Scalable Web Browsing via Tool-Augmented Programmatic Agent Pair

Xianghe Pang, Shuo Tang, Rui Ye +3

Effective information seeking in the vast and ever-growing digital landscape requires balancing expansive search with strategic reasoning. Current large language model (LLM)-based…

cs.AI20253 cited

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Rui Ye, Xiangrui Liu, Qimin Wu +4

LLM-based multi-agent systems (MAS) extend the capabilities of single LLMs by enabling cooperation among multiple specialized agents. However, most existing MAS frameworks rely on…

cs.SE2025

SWE-Dev: Evaluating and Training Autonomous Feature-Driven Software Development

Yaxin Du, Yuzhu Cai, Yifan Zhou +6

Large Language Models (LLMs) have shown strong capability in diverse software engineering tasks. However, feature-driven development, a highly prevalent real-world task that involv…

cs.LG2025

VLMGuard-R1: Proactive Safety Alignment for VLMs via Reasoning-Driven Prompt Optimization

Menglan Chen, Xianghe Pang, Jingjing Dong +3

Aligning Vision-Language Models (VLMs) with safety standards is essential to mitigate risks arising from their multimodal complexity, where integrating vision and language unveils…

cs.CL20249 cited

Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer Review

Rui Ye, Xianghe Pang, Jingyi Chai +6

Scholarly peer review is a cornerstone of scientific advancement, but the system is under strain due to increasing manuscript submissions and the labor-intensive nature of the proc…

cs.CR2024

SafeAgentBench: A Benchmark for Safe Task Planning of Embodied LLM Agents

Sheng Yin, Xianghe Pang, Yuanzhuo Ding +7

With the integration of large language models (LLMs), embodied agents have strong capabilities to understand and plan complicated natural language instructions. However, a foreseea…