14 papers
EntroRouter: Learning Efficient Model Routing via Entropy Regulation
Kaiyi Zhang, Xueliang Zhao, Zhuocheng Gong +2
Model routing balances solution accuracy and computational cost by selecting among models of varying capabilities. While recent multi-round frameworks interleave reasoning and plan…
Redesign Mixture-of-Experts Routers with Manifold Power Iteration
Songhao Wu, Ang Lv, Ruobing Xie +1
Router is the cornerstone component to the Mixture-of-Experts models. Serving as expert proxies, the rows of the router matrix compute their similarity to the MoE inputs to determi…
Rethinking Continual Experience Internalization for Self-Evolving LLM Agents
Jingwen Chen, Wenkai Yang, Shengda Fan +7
Experience internalization converts contextual experience from past interactions into reusable parametric capability, offering a promising path toward continual learning in large l…
DelTA: Discriminative Token Credit Assignment for Reinforcement Learning from Verifiable Rewards
Kaiyi Zhang, Wei Wu, Yankai Lin
Reinforcement learning from verifiable rewards (RLVR) has emerged as a central technique for improving the reasoning capabilities of large language models. Despite its effectivenes…
Less Noise, More Voice: Reinforcement Learning for Reasoning via Instruction Purification
Yiju Guo, Tianyi Hu, Zexu Sun +1
Reinforcement Learning with Verifiable Rewards (RLVR) has advanced LLM reasoning, but remains constrained by inefficient exploration under limited rollout budgets, leading to low s…
Forest Before Trees: Latent Superposition for Efficient Visual Reasoning
Yubo Wang, Juntian Zhang, Yichen Wu +3
While Chain-of-Thought empowers Large Vision-Language Models with multi-step reasoning, explicit textual rationales suffer from an information bandwidth bottleneck, where continuou…