256 citations · 314 across the 17 of their papers we have counts for
9 papers · 1 filter
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…
Subspace Defense: Discarding Adversarial Perturbations by Learning a Subspace for Clean Signals
Rui Zheng, Yuhao Zhou, Zhiheng Xi +3
Deep neural networks (DNNs) are notoriously vulnerable to adversarial attacks that place carefully crafted perturbations on normal examples to fool DNNs. To better understand such…
EasyJailbreak: A Unified Framework for Jailbreaking Large Language Models
Weikang Zhou, Xiao Wang, Limao Xiong +18
Jailbreak attacks are crucial for identifying and mitigating the security vulnerabilities of Large Language Models (LLMs). They are designed to bypass safeguards and elicit prohibi…
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…
RoCoIns: Enhancing Robustness of Large Language Models through Code-Style Instructions
Yuansen Zhang, Xiao Wang, Zhiheng Xi +4
Large Language Models (LLMs) have showcased remarkable capabilities in following human instructions. However, recent studies have raised concerns about the robustness of LLMs when…
StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback
Shihan Dou, Yan Liu, Haoxiang Jia +14
The advancement of large language models (LLMs) has significantly propelled the field of code generation. Previous work integrated reinforcement learning (RL) with compiler feedbac…
MouSi: Poly-Visual-Expert Vision-Language Models
Xiaoran Fan, Tao Ji, Changhao Jiang +21
Current large vision-language models (VLMs) often encounter challenges such as insufficient capabilities of a single visual component and excessively long visual tokens. These issu…
Secrets of RLHF in Large Language Models Part II: Reward Modeling
Binghai Wang, Rui Zheng, Lu Chen +24
Reinforcement Learning from Human Feedback (RLHF) has become a crucial technology for aligning language models with human values and intentions, enabling models to produce more hel…