…To prevent repeated local updates from causing skill drift, SKILL-KD further maintains trace-linked edit histories and performs Drift-Aware Skill Consolidation , deciding whether each patch should add a new rule…
…To better align training with this decoupled formulation, we further introduce Perception-Reasoning Alternating GRPO (PRA-GRPO), a role-aware reinforcement learning strategy that alternates between perception-focused and reasoning-focused updates…
…Learning Policies by Repairing Executable Knowledge Bases (2026) CoCoDA: Co-evolving Compositional DAG for Tool-Augmented Agents (2026) Formal Skill: Programmable Runtime Skills for Efficient and Accurate LLM Agents (2026) JTPRO: A…
…model to recover masked entities after multiple rounds of memory updates, thereby encouraging memory maintenance from the final outcome perspective; and (2) an intermediate memory recall objective , which requires the model to…
…DataEvolver treats data construction as feedback-driven construction policy evolution. A Retriever collects candidate samples, a Verifier assigns quality scores and rejection causes, a Critic summarizes round-level feedback into semantic feedback…
…supervised models that treat the conditioning signal as a static cue and ignore alignment information at inference, and guidance-based methods that consult it through hand-tuned linear updates, typically trading fidelity…
…training by anchoring functional tokens with a statically weighted auxiliary objective , providing stronger gradient updates . Extensive experiments and analyses demonstrate that ATLAS achieves superior performance on challenging benchmarks while maintaining clear interpretability…
…a 3D variational autoencoder compresses each volume, and a rectified-flow transformer generates in the latent space. Generation is conditioned on structured radiological metadata (18 abnormality findings, sex, age, and reconstruction kernel…
…BDH layer dimensions, exact update rules, and implementation details (Sec 3.3) Complete internal training recipe, hyperparameters, and augmentations (Sec 4.1–4.2) Additionally, there are no baseline comparisons (Transformer/Mamba…
…Improving Structured Output Reliability in Small Language Models (2026) Prompting Policies for Multi-step Reasoning and Tool-Use in Black-box LLMs with Iterative Distillation of Experience (2026) Prompt Codebooks: Discrete Compositional…