3 citations · 7 across the 4 of their papers we have counts for
4 papers
AgentGym: Evolving Large Language Model-based Agents across Diverse Environments
Zhiheng Xi, Yiwen Ding, Wenxiang Chen +17
Building generalist agents that can handle diverse tasks and evolve themselves across different environments is a long-term goal in the AI community. Large language models (LLMs) a…
Self-Demos: Eliciting Out-of-Demonstration Generalizability in Large Language Models
Wei He, Shichun Liu, Jun Zhao +6
Large language models (LLMs) have shown promising abilities of in-context learning (ICL), adapting swiftly to new tasks with only few-shot demonstrations. However, current few-shot…
Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
Zhiheng Xi, Wenxiang Chen, Boyang Hong +18
In this paper, we propose R: Learning Reasoning through Reverse Curriculum Reinforcement Learning (RL), a novel method that employs only outcome supervision to achieve the bene…
LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration
Jun Zhao, Can Zu, Hao Xu +6
Large language models (LLMs) have demonstrated impressive performance in understanding language and executing complex reasoning tasks. However, LLMs with long context windows have…