CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents Paper • 2603.17829 • Published Mar 18 • 1
CodeScout Collection RL-trained code search agents (1.7B, 4B, 14B) that outperform 2–18× larger models using only a Unix terminal. 📄 arxiv.org/abs/2603.17829 • 12 items • Updated Mar 19 • 10
SegDINO3D: 3D Instance Segmentation Empowered by Both Image-Level and Object-Level 2D Features Paper • 2509.16098 • Published Sep 19, 2025 • 1
Multi-Agent Deep Research: Training Multi-Agent Systems with M-GRPO Paper • 2511.13288 • Published Nov 17, 2025 • 20
OBLIQ-IR: Training a Dense Retriever for Oblique Queries Paper • 2609.29649 • Published 25 days ago • 1
What Makes Interaction Trajectories Effective for Training Terminal Agents? Paper • 2606.03461 • Published Jun 2 • 4
LEGO-RL: Harness-Native Reinforcement Learning for Coding Agents Paper • 2608.17393 • Published Aug 18 • 27
SoftwareGym: Scaling Computer-Use Agent Training with Diverse Synthesized Software Environments Paper • 2610.12611 • Published 8 days ago • 106
An Empirical Study of Harness Design for Coding Agents Paper • 2609.20804 • Published 29 days ago • 95
Systematic Multi-Agent Vision-and-Language Navigation: Formulation, Benchmark, and Method Paper • 2609.35965 • Published 9 days ago • 12
ModularRSI: Modular and Generalizable Recursive Harness Self-Improvement Paper • 2609.14857 • Published Sep 14 • 106
view article Article Detecting Machine-Generated Code: Unveiling Patterns in AI-Generated Programming YerbaPage • Jul 2, 2025 • 3
view article Article Tokenmaxxing BERT: 50x faster tokenization huggingface • about 10 hours ago • 31
Simulation RL Envs Collection Real-world work rebuilt as deterministic RL simulations from seed data. Part 1: PortSimEnv v1, berth planning at the Port of Barcelona. • 6 items • Updated 2 days ago • 2
SmolDataEnvs Multi-harness RL Collection Try the three environments, follow the tutorial, and explore the datasets, models and historical RL/SFT results. • 22 items • Updated 8 days ago • 4
SemBridge: Language Transfer in Sparse Encoders via Multilingual Semantic Bridges Paper • 2605.26002 • Published May 25 • 6