10 papers
ASymPO: Asymmetric-Scale Policy Optimization for Asynchronous LLM Post-Training Without Behavior Information
Zehua Liu, Yuxuan Yao, Xiaojin Fu +2
Asynchronous reinforcement learning can improve language-model post-training throughput by decoupling response generation from policy optimization, but stale responses introduce di…
Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation
Yuxuan Yao, Yuxuan Chen, Hui Li +6
Multimodal Diffusion Transformers (MMDiTs) for text-to-image generation maintain separate text and image branches, with bidirectional information flow between text tokens and visua…
Economy of Minds: Emerging Multi-Agent Intelligence with Economic Interactions
Zhenting Qi, Huangyuan Su, Ao Qu +13
How can a population of agents self-orchestrate and self-adapt into stronger collective intelligence without centralized control? Inspired by Friedrich Hayek's economic theory of d…
The Thinking Pixel: Recursive Sparse Reasoning in Multimodal Diffusion Latents
Yuwei Sun, Yuxuan Yao, Hui Li +1
Diffusion models have achieved success in high-fidelity data synthesis, yet their capacity for more complex, structured reasoning like text following tasks remains constrained. Whi…
Merging Beyond: Streaming LLM Updates via Activation-Guided Rotations
Yuxuan Yao, Haonan Sheng, Qingsong Lv +11
The escalating scale of Large Language Models (LLMs) necessitates efficient adaptation techniques. Model merging has gained prominence for its efficiency and controllability. Howev…
Activation-Guided Consensus Merging for Large Language Models
Yuxuan Yao, Shuqi Liu, Zehua Liu +6
Recent research has increasingly focused on reconciling the reasoning capabilities of System 2 with the efficiency of System 1. While existing training-based and prompt-based appro…