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A Privileged Teacher That Only Scores Cannot Search: Critique-Conditioned On-Policy Self-Distillation for Reasoning
The study tests whether scoring signals in on-policy self-distillation localize errors and push probability away from erroneous student tokens. It reports that full-distribution KL and token log-ratio signals do…
Use and Disuse: Intent-Structured Experience Consolidation for Memory and Learning in LLM Agents
The preprint proposes Hippocam, a hierarchical memory and continual-learning architecture that organizes ongoing work as nested intents. Active context stays centered on the current intent, while completed intents are…
GeoReform: Reflective Formalization Evolution for Multimodal Geometry Problem Solving
The preprint proposes GeoReform, which treats geometric formalization as an optimizable policy rather than a fixed parser output. It collects failed rollouts, diagnoses representation defects, and mutates how entities…
Recursive Self-Improvement through Multi-Agent Self-Supervision
The work describes MASS, which alternates evolutionary workflow optimization with supervised fine-tuning on self-generated trajectories. The abstract reports discovery of multi-agent workflows and, over two cycles with…
ScienceClaw: Benchmarking Continual Self-Evolution of AI-for-Science Agents Across the Natural and Social Sciences
The preprint formalizes fixed-parameter program self-evolution that links task solving, scientific verification, and program updates. ScienceClaw-Eval spans 23 disciplines and measures correctness, evolutionary gain…
Sherpa: Teaching LLMs to Teach Adaptively
The preprint introduces Sherpa, a multi-turn reinforcement-learning framework that trains an LLM teacher against multiple student archetypes with distinct learning preferences. The teacher is optimized directly against…
VeriFine: Scaling Verification for Self-Improvement in Embodied Reasoning
The preprint proposes an agent harness that co-evolves the policy, training curriculum, and judge. A Policy Improvement Loop diagnoses recurring failures and builds an adaptive curriculum; when verification becomes a…
ImproveAnyTask: An Autonomous Post-Training Harness for Iterative Model Self-Improvement
The preprint describes an autonomous post-training harness that attributes errors, selects update directions, and executes model updates under a limited compute budget. It combines metric- and case-level analysis…
Credit Where It Matters: Dependency-Aware Policy Optimization for Terminal Agents
The preprint proposes Dependency-Aware Group Policy Optimization (DepGPO) for multi-step terminal tasks. It builds a command dependency graph from execution traces, traces backward from resources inspected by a…
Recursive Harness Self-Improvement for Frontier Reasoning Data Synthesis
The preprint introduces task-harness co-evolution for recursive reasoning-data synthesis. Online self-improvement turns solver failures into reusable skills, while post-task updates revise skills, prompts, and…
PivotOPD: Learning to Recover from Pivotal Mistakes in Multi-Turn Agents
The technical report studies pivotal mistakes that move an agent farther from task completion during multi-turn interaction. Across three Qwen3 models, the abstract reports that more than half of failed rollouts…
SAGE: Mitigating Long-Horizon Reasoning Biases via Topological Guidance
SAGE proposes Structural Admissibility-Guided Exploration for long-horizon reasoning under sparse rewards. It frames two failure modes—exploration bias toward locally plausible but unstable branches and compounding…
Self-Play Pretraining with Zero Data
The paper presents a proof-of-concept in which a generator and learner train in tandem without natural training data. The generator proposes programs interpreted by a universal Turing machine to produce byte sequences…
Harness-Zero: Harness Distillation via Agent-as-Harness
Harness-Zero uses a domain- or instance-optimized harness as training-time guidance, then transfers its behavior into model weights so the specialized harness can be removed at deployment. An agent-as-harness corrects…
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