…Evaluating AI Agents as Market Participants (2026) IEMAS: An Incentive-Efficiency Routing Framework for Open Agentic Web Ecosystems (2026) Can AI Models Direct Each Other? Organizational Structure as a Probe into Training…
…Quanhao Li , , , , , , , , , Abstract DiffusionOPD enables efficient multi-task training for diffusion models through online policy distillation, outperforming existing reinforcement learning approaches in both training efficiency and final performance. AI-generated summary Reinforcement…
…for Multi-Turn Agentic Training (2026) Beyond Where to Look: Trajectory-Guided Reinforcement Learning for Multimodal RLVR (2026) Too Correct to Learn: Reinforcement Learning on Saturated Reasoning Data (2026) Please give a…
…AI-generated summary Looped Transformers offer a promising alternative to purely feed-forward computation by iteratively refining latent representations , improving language modeling and reasoning. Yet recurrent architectures remain unstable to train, costly…
…No dataset linking this paper Cite arxiv.org/abs/2605.11400 in a dataset README.md to link it from this page. No Space linking this paper Cite arxiv.org/abs/2605…
…Abstract Stable-GFN addresses training instability and mode collapse in generative flow networks for large language model red-teaming through partition function elimination and robust masking techniques. AI-generated summary Large Language…
…which are addressed through a momentum-based approach that improves training efficiency and performance over existing models like Mamba2 and GDN. AI-generated summary Linear Attention (LA) offers a promising paradigm for…
…No dataset linking this paper Cite arxiv.org/abs/2605.12495 in a dataset README.md to link it from this page. No Space linking this paper Cite arxiv.org/abs/2605…
…AI-generated summary Federated learning is a machine learning paradigm in which multiple devices collaboratively train a model under the supervision of a central server while ensuring data privacy. However, its performance…
…a training-free generative reconstruction framework that uses video diffusion priors to synthesize novel views and recover complete 3D scenes from sparse inputs through adaptive denoising and iterative refinement. AI-generated summary…