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20232026
most citedUncertainty-Penalized Reinforcement Learning from Human Feedback with Diverse Reward LoRA Ensembles

1 citations · 2 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

TreeRef-BFN: Equivariance-Free De Novo Molecule Generation based on 2D Topology and Internal 3D Geometry

Ruiqing Sun, Sen Yang, Dawei Feng +3

De novo 3D molecular generation jointly models molecular size, topology, and geometry. Most methods pre-sample molecular size and generate Cartesian coordinates, limiting variable-…

cs.AI2026

MCPEvol-Bench: Benchmarking LLM Agent Performance Across Dynamic Evolutions of MCP Servers

Huanxi Liu, Kun Hu, Jiaqi Liao +6

As Model Context Protocol (MCP) servers emerge as the core infrastructure for connecting LLMs with external tools, existing benchmarks leverage real-world MCP servers to evaluate L…

cs.AI2026

Beyond Scores: Diagnostic LLM Evaluation via Fine-Grained Abilities

Xu Zhang, Xudong Gong, Jiacheng Qin +5

Current evaluations of large language models aggregate performance across diverse tasks into single scores. This obscures fine-grained ability variation, limiting targeted model im…

cs.AI2025

Pay More Attention to the Robustness of Prompt for Instruction Data Mining

Qiang Wang, Dawei Feng, Xu Zhang +4

Instruction tuning has emerged as a paramount method for tailoring the behaviors of LLMs. Recent work has unveiled the potential for LLMs to achieve high performance through fine-t…

cs.AI2024

Enhancing Decision-Making for LLM Agents via Step-Level Q-Value Models

Yuanzhao Zhai, Tingkai Yang, Kele Xu +4

Agents significantly enhance the capabilities of standalone Large Language Models (LLMs) by perceiving environments, making decisions, and executing actions. However, LLM agents st…