Papers

Filtered to hyperparameter tuning · clear filter

Browse by term

continual learning 83reinforcement learning 50large language models 12benchmarking 11benchmarks 11language models 11vision-language models 11robotics 7natural language processing 6world models 6generative models 5recursive self-improvement 5attention mechanisms 4diffusion Transformers 4multi-agent systems 4multimodal learning 4multimodal models 4on-policy distillation 4self-distillation 4self-supervised learning 4transformers 4video generation 4vision-language-action models 4agent-based systems 3agentic models 3agentic search 3autonomous systems 3coding agents 3diffusion models 3image generation 3

Matching papers

DataFlex-RL: An Evaluation Platform for RLVR Data Policies

109 upvotes · 5 SEP 2026 · Hao Liang, Mingrui Chen, Hengyi Feng et al.

This paper introduces DataFlex-RL, an evaluation platform for comparing different data policies in reinforcement learning with verifiable rewards (RLVR), and finds that uniform data policy leads to better performance and is more reproducible than other methods. Practitioners might care about this because it provides a way to compare different data policies and ensure that their RLVR models are performing well.

reinforcement learningverifiable rewardsdata policiesbenchmarkinghyperparameter tuning