From the 1 of 11 linked papers with an AI index.
11 papers
Energy-Structured Latent World Models with Neural Time Fields for Physically Constistent Open-World Motion Planning
Yapeng Liu, Yuanzhao Zhai, Bo Ding +2
Physically consistent motion planning remains a fundamental challenge in embodied AI, as generated trajectories must strictly conform to real-world execution dynamics. While latent…
MCPEvol-Bench: Benchmarking LLM Agent Performance Across Dynamic Evolutions of MCP Servers
Huanxi Liu, Kun Hu, Jiaqi Liao +6
The paper introduces MCPEvol-Bench, a benchmark that tests how well large language model agents adapt to changing tool interfaces and functionalities in Model Context Protocol (MCP…
Decoupling Constraints from Two Directions for Evolutionary Constrained Multi-objective Optimization
Ruiqing Sun, Dawei Feng, Xing Zhou +6
Real-world constrained multi-objective optimization problems (CMOPs) commonly involve multiple constraints, and understanding and exploiting their coupling relationships is crucial…
From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning
Kele Xu, Yulu Fang, Boda Zhou +6
This paper examines audio self-supervised learning (SSL) through the alignment between pretraining objectives, architectural inductive biases, and downstream applications. Rather t…
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…
Scaffold-Conditioned Preference Triplets for Controllable Molecular Optimization with Large Language Models
Yi Xiong, Liang Xiong, Xiaohong Ji +4
Molecular property optimization is central to drug discovery, yet many deep learning methods rely on black-box scoring and offer limited control over scaffold preservation, often p…