Learning from the Self-future: On-policy Self-distillation for dLLMs Paper • 2606.18195 • Published Jun 16 • 175
HarnessDev: Can LLMs Create and Evolve Their Own Agent Harness? Paper • 2609.01437 • Published Sep 1 • 569
NeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness Paper • 2609.08183 • Published about 1 month ago • 328
ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation Paper • 2609.03756 • Published Sep 3 • 25
Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget Paper • 2607.13125 • Published Jul 18 • 140
The Mirage of Optimizing Training Policies: Monotonic Inference Policies as the Real Objective for LLM Reinforcement Learning Paper • 2606.29526 • Published Jun 28 • 52
AI translation of literary texts is "fine", but readers still prefer human translations Paper • 2606.26040 • Published Jun 24 • 6
When Does Multi-Agent RL Improve LLM Workflows? Workflow, Scale, and Policy-Sharing Tradeoffs Paper • 2605.24202 • Published May 22 • 17
Crafter: A Multi-Agent Harness for Editable Scientific Figure Generation from Diverse Inputs Paper • 2605.30611 • Published May 28 • 65
Claw-Anything: Benchmarking Always-On Personal Assistants with Broader Access to User's Digital World Paper • 2605.26086 • Published May 25 • 26
Mean Mode Screaming: Mean--Variance Split Residuals for 1000-Layer Diffusion Transformers Paper • 2605.06169 • Published May 7 • 57
Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models Paper • 2604.08545 • Published Apr 9 • 41
Adam's Law: Textual Frequency Law on Large Language Models Paper • 2604.02176 • Published Apr 2 • 109
Training a Student Expert via Semi-Supervised Foundation Model Distillation Paper • 2604.03841 • Published Apr 4 • 10
Video Models Reason Early: Exploiting Plan Commitment for Maze Solving Paper • 2603.30043 • Published Mar 31 • 13