most citedTraining Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning

2 citations · 3 across the 3 of their papers we have counts for

collaborators

3 papers

cs.SE2024★ 1 cited

Multi-Programming Language Sandbox for LLMs

Shihan Dou, Jiazheng Zhang, Jianxiang Zang +25

We introduce MPLSandbox, an out-of-the-box multi-programming language sandbox designed to provide unified and comprehensive feedback from compiler and analysis tools for Large Lang…

cs.CL2024

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…

cs.AI2024★ 2 cited

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…