Weekly Releases (Oct 26–Nov 01, 2026) Collection Repositories created 2026-10-26 through 2026-11-01 (Europe/Istanbul); models/Spaces 15+ likes, datasets 10+ likes. • 83 items • Updated 3 days ago • 3
MemoryWalker: Stop Training Agents on Contexts They Never Saw Paper • 2609.00865 • Published Sep 1 • 1
Memento 3: Model-Based Recursive Self-Improvement through Reflective Rulebooks Paper • 2610.11794 • Published 29 days ago • 37
Agentic Memory Management Is the Next Frontier of Information Retrieval Paper • 2610.32464 • Published 14 days ago • 1
Is Complex Agentic Memory Always Needed? Naive RAG Is Stronger Than We Thought Paper • 2610.30755 • Published 15 days ago • 22
LFM2.5-24B Harness adapters Collection A collection of models trained with RL on specific adapters for more efficient agentic development • 6 items • Updated 4 days ago • 24
WorkFactory: Turning Professional Intents into Executable Work for Scalable Agent Training Paper • 2610.37161 • Published 10 days ago • 41
Your LR Schedule May Not Be Principled: Effective Learning Rate Scheduling in Weight-Normalized Training Paper • 2610.40362 • Published 8 days ago • 11
On-Policy Self-Training: Data-Free Self-Improvement in Large Language Models Paper • 2610.32770 • Published 14 days ago • 31
Continual Learning Exam: Benchmarking Long-Horizon RSI and Experiential Learning in LLM Agents Paper • 2610.33956 • Published 12 days ago • 35
Work Agents: Systems, Capabilities, and Optimization Paper • 2610.35845 • Published 11 days ago • 115
Trajectory2Gym: Decision-Grounded Compositional Interaction Synthesis for Tool-Use Agents Paper • 2610.33568 • Published 13 days ago • 39
Spark-X2.6 Collection SOTA On-Device LLMs. Advancing the Frontier of On-Device Agents for Real-World Tasks. • 14 items • Updated 5 days ago • 43
DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression Paper • 2609.19969 • Published Sep 17 • 203
Every Step Evolves: Scaling Reinforcement Learning for Trillion-Scale Thinking Model Paper • 2510.18855 • Published Oct 21, 2025 • 74
MoESQ Collection Paired-4:8 + NVFP4 W4A4 expert compressed MoE models for NVIDIA Blackwell Sparse Tensor Cores. • 6 items • Updated 15 days ago • 6