5 papers · 1 filter
U-Fold: Dynamic Intent-Aware Context Folding for User-Centric Agents
Jin Su, Runnan Fang, Yeqiu Li +5
Large language model (LLM)-based agents have been successfully deployed in many tool-augmented settings, but their scalability is fundamentally constrained by context length. Exist…
AutoForge: Automated Environment Synthesis for Agentic Reinforcement Learning
Shihao Cai, Runnan Fang, Jialong Wu +10
Conducting reinforcement learning (RL) in simulated environments offers a cost-effective and highly scalable way to enhance language-based agents. However, previous work has been l…
Towards General Agentic Intelligence via Environment Scaling
Runnan Fang, Shihao Cai, Baixuan Li +13
Advanced agentic intelligence is a prerequisite for deploying Large Language Models in practical, real-world applications. Diverse real-world APIs demand precise, robust function-c…
SynWorld: Virtual Scenario Synthesis for Agentic Action Knowledge Refinement
Runnan Fang, Xiaobin Wang, Yuan Liang +8
In the interaction between agents and their environments, agents expand their capabilities by planning and executing actions. However, LLM-based agents face substantial challenges…
Agentic Knowledgeable Self-awareness
Shuofei Qiao, Zhisong Qiu, Baochang Ren +8
Large Language Models (LLMs) have achieved considerable performance across various agentic planning tasks. However, traditional agent planning approaches adopt a "flood irrigation"…