activity
20232026
most citedFrom Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning

4 citations · 7 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2026

BRIDGE: Selective Boundary Repair with Dependency Graph Evidence in Multi-Agent Systems

Encheng Su, Pengze Li, Ziheng Hua +11

Multi-agent collaboration has emerged as a critical paradigm for tackling complex, long-horizon tasks; however, while coordination protocols continue to advance, systemic failures…

cs.CE2026

PROTEAN: Beyond De Novo Generation - Can LLM Agents Perform Text-Guided Protein Structure Editing?

Encheng Su, Xinping Liu, Yizhou Wang +11

Generative AI has achieved remarkable success in de novo protein design, yet protein engineering typically begins with existing, characterized proteins. The primary demand is targe…

cs.AI2026

SciIF: Benchmarking Scientific Instruction Following Towards Rigorous Scientific Intelligence

Encheng Su, Jianyu Wu, Chen Tang +9

As large language models (LLMs) transition from general knowledge retrieval to complex scientific discovery, their evaluation standards must also incorporate the rigorous norms of…

cs.CL2025★ 1 cited

MOOSE-Chem3: Toward Experiment-Guided Hypothesis Ranking via Simulated Experimental Feedback

Wanhao Liu, Zonglin Yang, Jue Wang +7

Hypothesis ranking is vital for automated scientific discovery, especially in cost-intensive, throughput-limited natural science domains. Current methods focus on pre-experiment ra…

cs.CL2024★ 4 cited

From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning

Wei Chen, Zhen Huang, Liang Xie +9

Large Language Models (LLMs) tend to prioritize adherence to user prompts over providing veracious responses, leading to the sycophancy issue. When challenged by users, LLMs tend t…

cs.CV2023★ 1 cited

TinySAM: Pushing the Envelope for Efficient Segment Anything Model

Han Shu, Wenshuo Li, Yehui Tang +5

Recently segment anything model (SAM) has shown powerful segmentation capability and has drawn great attention in computer vision fields. Massive following works have developed var…

cs.CV2023★ 1 cited

MSight: An Edge-Cloud Infrastructure-based Perception System for Connected Automated Vehicles

Rusheng Zhang, Depu Meng, Shengyin Shen +3

As vehicular communication and networking technologies continue to advance, infrastructure-based roadside perception emerges as a pivotal tool for connected automated vehicle (CAV)…