3 citations · 3 across the 7 of their papers we have counts for
8 papers
On-Policy Residual Learning for Diffusion Language Models
Yifan Yu, Yuqing Jian, Jisen Li +9
Residual context is key to unlocking the speed-quality Pareto frontier of diffusion language models (DLMs) by carrying forward predictive distributions across denoising steps. Yet…
Osprey: Target-agnostic Pre-training Makes Stronger Drafters in Speculative Decoding
Fengxiang Bie, Yuqing Jian, Yifan Yu +7
Speculative decoding is critical for accelerating LLM inference. However, the speedup is fragile: drafters are typically trained against a narrow distribution for a single target m…
Introspective Diffusion Language Models
Yifan Yu, Yuqing Jian, Junxiong Wang +12
Diffusion language models promise parallel generation, yet still lag behind autoregressive (AR) models in quality. We stem this gap to a failure of introspective consistency: AR mo…
XRPO: Pushing the limits of GRPO with Targeted Exploration and Exploitation
Udbhav Bamba, Minghao Fang, Yifan Yu +2
Reinforcement learning algorithms such as GRPO have driven recent advances in large language model (LLM) reasoning. While scaling the number of rollouts stabilizes training, existi…
OPPO: Accelerating PPO-based RLHF via Pipeline Overlap
Kaizhuo Yan, Yingjie Yu, Yifan Yu +2
Proximal Policy Optimization (PPO)-based reinforcement learning from human feedback (RLHF) is a widely adopted paradigm for aligning large language models (LLMs) with human prefere…
CORRECT: COndensed eRror RECognition via knowledge Transfer in multi-agent systems
Yifan Yu, Moyan Li, Shaoyuan Xu +4
Multi-agent systems (MAS) are increasingly capable of tackling complex real-world tasks, yet their reliance on inter-agent coordination, tool use, and long-horizon reasoning makes…
Single-agent or Multi-agent Systems? Why Not Both?
Mingyan Gao, Yanzi Li, Banruo Liu +4
Multi-agent systems (MAS) decompose complex tasks and delegate subtasks to different large language model (LLM) agents and tools. Prior studies have reported the superior accuracy…
IC-Cache: Efficient Large Language Model Serving via In-context Caching
Yifan Yu, Yu Gan, Nikhil Sarda +7
Large language models (LLMs) have excelled in various applications, yet serving them at scale is challenging due to their substantial resource demands and high latency. Our real-wo…