5 papers
DASH-OPD: Discrepancy-Aware Switching with Hysteresis for On-Policy Distillation
Yuchen Xia, Qianguo Sun, Chao Song +3
While on-policy distillation (OPD) reduces exposure bias by training student language models on their own rollouts, early student errors in long-horizon agentic scenarios can lead…
Demystifying Reinforcement Learning for Long-Horizon Tool-Using Agents: A Comprehensive Recipe
Xixi Wu, Qianguo Sun, Ruiyang Zhang +4
Reinforcement Learning (RL) is essential for evolving Large Language Models (LLMs) into autonomous agents capable of long-horizon planning, yet a practical recipe for scaling RL in…
VSearcher: Long-Horizon Multimodal Search Agent via Reinforcement Learning
Ruiyang Zhang, Qianguo Sun, Chao Song +2
Large models are increasingly becoming autonomous agents that interact with real-world environments and use external tools to augment their static capabilities. However, most recen…
Linear Preference Optimization: Decoupled Gradient Control via Absolute Regularization
Rui Wang, Qianguo Sun, Chao Song +4
DPO (Direct Preference Optimization) has become a widely used offline preference optimization algorithm due to its simplicity and training stability. However, DPO is prone to overf…
UniTTS: An end-to-end TTS system without decoupling of acoustic and semantic information
Rui Wang, Qianguo Sun, Tianrong Chen +3
The emergence of multi-codebook neutral audio codecs such as Residual Vector Quantization (RVQ) and Group Vector Quantization (GVQ) has significantly advanced Large-Language-Model…