6 papers
ToolGate: Token-Efficient Pre-Call Control for Tool-Augmented Vision-Language Agents
Anjie Liu, Yan Song, Zhixun Chen +3
Tool-augmented vision-language agents can acquire external perceptual evidence through OCR, detection, segmentation, and other tools, but executing every proposed tool call is cost…
Memento-Skills: Let Agents Design Agents
Huichi Zhou, Siyuan Guo, Anjie Liu +14
We introduce \emph{Memento-Skills}, a generalist, continually-learnable LLM agent system that functions as an \emph{agent-designing agent}: it autonomously constructs, adapts, and…
MuRating: A High Quality Data Selecting Approach to Multilingual Large Language Model Pretraining
Zhixun Chen, Ping Guo, Wenhan Han +10
Data quality is a critical driver of large language model performance, yet existing model-based selection methods focus almost exclusively on English. We introduce MuRating, a scal…
Social World Model-Augmented Mechanism Design Policy Learning
Xiaoyuan Zhang, Yizhe Huang, Chengdong Ma +6
Designing adaptive mechanisms to align individual and collective interests remains a central challenge in artificial social intelligence. Existing methods often struggle with model…
MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages
Wenhan Han, Yifan Zhang, Zhixun Chen +7
Multilingual large language models (LLMs) are advancing rapidly, with new models frequently claiming support for an increasing number of languages. However, existing evaluation dat…
ATLaS: Agent Tuning via Learning Critical Steps
Zhixun Chen, Ming Li, Yuxuan Huang +3
Large Language Model (LLM) agents have demonstrated remarkable generalization capabilities across multi-domain tasks. Existing agent tuning approaches typically employ supervised f…