Tail-Likelihood Reinforcement Learning

arXiv:2609.02987 · cs.LG, stat.ML · Submitted 2026-09-02 · Read on arXiv

cs.LG, stat.ML

Submitted: 2026-09-02

Updated: 2026-09-09

Project page: https://zanette-labs.github.io/TailRL-website

Terminology

• GRPO — 58× in this paper · explained in 6 episodes
• Reinforcement Learning — 53× in this paper · explained in 4 episodes
• Grounding — 26× in this paper · explained in 3 episodes
• Reward Function — 9× in this paper · explained in 2 episodes
• In International Conference on Machine Learning — 8× in this paper
• Accuracy — 7× in this paper · explained in 1 episode
• In International Conference on Learning Representations — 6× in this paper
• Adam — 5× in this paper · explained in 2 episodes
• Regularization — 5× in this paper · explained in 3 episodes
• KL Regularization — 4× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• Deep Reinforcement Learning — 3× in this paper · explained in 2 episodes
• Meeting of the Association for Computational Linguistics — 3× in this paper
• Benchmark — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• In Conference on Language Modeling — 2× in this paper
• Mode Collapse — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Verifiable Rewards — 2× in this paper · explained in 2 episodes
• Adaptive Sampling — 1× in this paper · explained in 1 episode
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Entropy Collapse — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• In European Conference on Computer Vision — 1× in this paper
• Information Gain — 1× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Shaping — 1× in this paper · explained in 2 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes
• TailRL on Vision Language Models — 1× in this paper
• Test-time Scaling — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Qwen2.5-VL Technical Report
• Kevin: Multi-Turn RL for Generating CUDA Kernels
• Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
• Evaluating Large Language Models Trained on Code
• Self-Evolving Curriculum for LLM Reasoning
• Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models
• Robust Reinforcement Learning with Distributional Risk-averse formulation
• Training Verifiers to Solve Math Word Problems
• The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models
• CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
• What is the objective of reasoning with reinforcement learning?
• StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback
• Differential Smoothing Mitigates Sharpening and Improves LLM Reasoning
• KL-Regularized Reinforcement Learning is Designed to Mode Collapse
• Target Policy Optimization
• CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning
• Let's Verify Step by Step
• RLTF: Reinforcement Learning from Unit Test Feedback
• The gem5 Simulator: Version 20.0+
• The Reasoning Boundary Paradox: How Reinforcement Learning Constrains Language Models

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