1 citations · 2 across the 11 of their papers we have counts for
6 papers · 1 filter
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-…
Resilience Matters for Embodied Agents System: New Metrics, Systematic Evaluation, and Optimization
Yapeng Liu, Yuanzhao Zhai, Xudong Gong +4
Embodied Agents System (EAS) are increasingly deployed in open-world physical domains, where reliability directly dictates deployment quality and human-agent trust. However, existi…
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…
ParetoPilot: Zero-Surrogate Offline Multi-Objective Optimization via Infer-Perturb-Guide Diffusion
Ruiqing Sun, Sen Yang, Dawei Feng +3
Offline multi-objective optimization (Offline MOO) seeks Pareto-optimal designs from static datasets without additional environment interactions. Existing generative methods typica…
MAny: Merge Anything for Multimodal Continual Instruction Tuning
Zijian Gao, Wangwang Jia, Xingxing Zhang +6
Multimodal Continual Instruction Tuning (MCIT) is essential for sequential task adaptation of Multimodal Large Language Models (MLLMs) but is severely restricted by catastrophic fo…
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…