26 citations · 67 across the 14 of their papers we have counts for
17 papers
OpenRFT: Adapting Reasoning Foundation Model for Domain-specific Tasks with Reinforcement Fine-Tuning
Yuxiang Zhang, Yuqi Yang, Jiangming Shu +3
OpenAI's recent introduction of Reinforcement Fine-Tuning (RFT) showcases the potential of reasoning foundation model and offers a new paradigm for fine-tuning beyond simple patter…
o1-Coder: an o1 Replication for Coding
Yuxiang Zhang, Shangxi Wu, Yuqi Yang +4
The technical report introduces O1-CODER, an attempt to replicate OpenAI's o1 model with a focus on coding tasks. It integrates reinforcement learning (RL) and Monte Carlo Tree Sea…
A Disguised Wolf Is More Harmful Than a Toothless Tiger: Adaptive Malicious Code Injection Backdoor Attack Leveraging User Behavior as Triggers
Shangxi Wu, Jitao Sang
In recent years, large language models (LLMs) have made significant progress in the field of code generation. However, as more and more users rely on these models for software deve…
Semantically consistent Video-to-Audio Generation using Multimodal Language Large Model
Gehui Chen, Guan'an Wang, Xiaowen Huang +1
Existing works have made strides in video generation, but the lack of sound effects (SFX) and background music (BGM) hinders a complete and immersive viewer experience. We introduc…
Exploring the Privacy Protection Capabilities of Chinese Large Language Models
Yuqi Yang, Xiaowen Huang, Jitao Sang
Large language models (LLMs), renowned for their impressive capabilities in various tasks, have significantly advanced artificial intelligence. Yet, these advancements have raised…
How Reliable is Your Simulator? Analysis on the Limitations of Current LLM-based User Simulators for Conversational Recommendation
Lixi Zhu, Xiaowen Huang, Jitao Sang
Conversational Recommender System (CRS) interacts with users through natural language to understand their preferences and provide personalized recommendations in real-time. CRS has…