After each batch, an optimizer proposes an update from scored trajectories. Instead of relying on a fixed validation set, the update is tested on new and past cases and kept only if it helps on new ...
Cite arxiv.org/abs/2610.12341 in a model README.md to link it from this page.
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Join the discussion on this paper page Beyond Spatio-Temporal Priors: A Generalizable Approach for Dense Correspondence Matching ...
Join the discussion on this paper page MiMo-V2.6: Scaling Reinforcement Learning Towards Self-Improvement ...
Join the discussion on this paper page Remory appends learned soft memory tokens to a compacted summary. On Qwen3.8-27B and GLM-5.3-Flash, it improves long-horizon benchmark performance while reducing ...
Join the discussion on this paper page OneSearch-VL: Unified Multimodal Deep Research Agent for Image and Video ...
Join the discussion on this paper page TestPrism: Rethinking Test Evaluation Beyond a Single Reference ...
Join the discussion on this paper page Learn2Play Bench: How Well Do LLM Agents Learn from Experience in Unfamiliar Environments?
Join the discussion on this paper page TokenRouter: Efficient Serving System for Token-Level LLM Routing ...
Join the discussion on this paper page SuperNav: An Agentic Navigation System for Any Task in Any Scene ...
Join the discussion on this paper page SparseDecoding: Decoding-Aware Pruning for Accurate and Efficient LLM Inference ...
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