Papers

Filtered to task-specific input · clear filter

Browse by term

continual learning 91reinforcement learning 43vision-language models 18benchmarking 12benchmarks 11robotics 11large language models 10language models 9world models 9video generation 6generative models 5multimodal models 5natural language processing 5recursive self-improvement 5video world models 5agents 4dialogue systems 4diffusion models 4foundation models 4multimodal large language models 4on-policy distillation 4reasoning 4self-distillation 4self-supervised learning 4conversational AI 3evaluation benchmarks 3human-computer interaction 3LLMs 3multi-agent systems 3policy optimization 3

Matching papers

CodeMidas: Scaling Agentic Coding RL Environments from Code Itself

82 upvotes · 18 SEP 2026 · Bowen Ye, Lei Li, Shicheng Li et al.

This paper creates a system called CodeMidas that turns existing open-source code into environments for training coding agents using reinforcement learning. Practitioners might care because it could lead to more diverse and effective coding agents that can learn to fix issues, construct code, and verify their own work.