Papers

Filtered to trajectory balance · clear filter

Browse by term

continual learning 86reinforcement learning 48benchmarking 13large language models 12benchmarks 11vision-language models 10language models 9robotics 7world models 7natural language processing 6recursive self-improvement 6generative models 5on-policy distillation 5video generation 5attention mechanisms 4coding agents 4LLMs 4multi-agent systems 4multimodal learning 4multimodal models 4self-distillation 4self-supervised learning 4transformers 4vision-language-action models 4world modeling 4agent-based systems 3agentic models 3agentic search 3agents 3autonomous systems 3

Matching papers

FlowBalance: Verifier-Grounded Self-Improvement from On-Policy Reasoning Experience

52 upvotes · 3 SEP 2026 · Zixun Huang, Kishan Panaganti, Haitao Mi et al.

This paper introduces FlowBalance, a method that helps a reasoning model improve itself by learning from its own experiences, while avoiding overconfidence and focusing on the best solutions. Practitioners might care about this approach because it can lead to more accurate and diverse model performance.