mlsanityData to 7 Oct 2026

Off-Context GRPO: Learning to Reason on Hard Problems using Privileged Information

arXiv 2607.19313 ↗First posted 21 Jul 2026cs.LG cs.AIcited by 6

On the map: LLM reasoning → Reinforcement learning for reasoning

Abstract (arXiv)

Reinforcement learning with verifiable rewards (RLVR) improves reasoning in large language models. Yet, typical RLVR approaches fail on difficult problems: when a model cannot generate any correct solutions, it receives textitzero learning signal. Providing privileged guidance during training, such as solution prefixes, can help overcome this learning cliff by steering the model towards correct solutions with non-zero reward. We call these rollouts textitoff-context: they are generated from a training prompt that contains privileged guidance, while the target objective is defined by the original prompt without that guidance. We introduce Off-Context GRPO (OC-GRPO), a minimally modified variant of GRPO that uses guided rollouts but applies an importance-corrected objective to steer the update back toward the original unguided objective, avoiding the mismatch that destabilizes uncorrected guided training. Empirically, our algorithm achieves a 3.8% absolute improvement (13.7% relative gain) over vanilla GRPO on average across standard mathematical reasoning benchmarks with negligible additional cost.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Placed in Reinforcement learning for reasoning, one of 17 directions in LLM reasoning. Builds on 38 of its 46 references that are in the map. First posted on arXiv 21 Jul 2026.

Builds on

38 of 46 references.

Closest ancestors · 18

Same direction, newest first

  1. 2026Reuse your FLOPs: Scaling RL on Hard Problems by Conditioning on Very Off-Policy Prefixes26 Jan
  2. 2026POPE: Learning to Reason on Hard Problems via Privileged On-Policy Exploration26 Jan
  3. 2025AdaCuRL: Adaptive Curriculum Reinforcement Learning with Invalid Sample Mitigation and Historical Revisiting12 Nov
  4. 2025Scaf-GRPO: Scaffolded Group Relative Policy Optimization for Enhancing LLM Reasoning22 Oct
  5. 2025ExGRPO: Learning to Reason from Experience2 Oct
  6. 2025CLPO: Curriculum Learning meets Policy Optimization for LLM Reasoning29 Sep
  7. 2025VCRL: Variance-based Curriculum Reinforcement Learning for Large Language Models24 Sep
  8. 2025Staying in the Sweet Spot: Responsive Reasoning Evolution via Capability-Adaptive Hint Scaffolding8 Sep
  9. 2025Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration19 Aug
  10. 2025G2RPO-A: Guided Group Relative Policy Optimization with Adaptive Guidance18 Aug
  11. 2025StepHint: Multi-level Stepwise Hints Enhance Reinforcement Learning to Reason3 Jul
  12. 2025Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling2 Jul
6 more
  1. 2025BREAD: Branched Rollouts from Expert Anchors Bridge SFT & RL for Reasoning20 Jun
  2. 2025Self-Evolving Curriculum for LLM Reasoning20 May
  3. 2025Learning to Reason under Off-Policy Guidance21 Apr
  4. 2025DUMP: Automated Distribution-Level Curriculum Learning for RL-based LLM Post-training13 Apr
  5. 2025DAPO: An Open-Source LLM Reinforcement Learning System at Scale18 Mar
  6. 2017Proximal Policy Optimization Algorithms20 Jul

Other references · 20

  1. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 8,851
  2. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  3. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,767
  4. 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,203
  5. 2024HybridFlow: A Flexible and Efficient RLHF Frameworkcited by 1,980
  6. 2017Hindsight Experience Replaycited by 1,096
  7. 2022STaR: Bootstrapping Reasoning With Reasoningcited by 895
  8. 2023On-Policy Distillation of Language Models: Learning from Self-Generated Mistakescited by 840
  9. 2026Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Modelscited by 386
  10. 2023Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Modelscited by 325
  11. 2026Reinforcement Learning via Self-Distillationcited by 285
  12. 2024Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Modelscited by 277
8 more
  1. 2025MathArena: Evaluating LLMs on Uncontaminated Math Competitionscited by 275
  2. 2024Trial and Error: Exploration-Based Trajectory Optimization for LLM Agentscited by 194
  3. 2023Evaluating the Performance of Large Language Models on GAOKAO Benchmarkcited by 182
  4. 2025On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weightingcited by 88
  5. 2026GATES: Self-Distillation under Privileged Context with Consensus Gatingcited by 30
  6. 2025RL for Reasoning by Adaptively Revealing Rationalescited by 15
  7. 2026AgentHER: Hindsight Experience Replay for LLM Agent Trajectory Relabelingcited by 13
  8. 2025Sample-Efficient Online Learning in LM Agents via Hindsight Trajectory Rewritingcited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 6.

6 papers.

  1. 2026Hints, Critics, and Teachers: Prior Injection for Sparse-Reward RL in Vision-Language Math Reasoningcited by 0
  2. 2026The Model Knows Another Way: Strategy Switching for Effective RLVR Explorationcited by 0
  3. 2026Save Your Saturated Data: Learning Beyond Reward Saturation in Group-Based RLcited by 0
  4. 2026RAISE: Reinforcing Access Control Policy Synthesis in LLMs via Symbolic Evaluationcited by 0
  5. 2026RLTL;DR: Self-improvement by Internalizing Self-generated Feedbackcited by 0
  6. 2026Unlearnable, or Unmeasured? On the Reliability of Difficulty Labels in RLVRcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Can GRPO Help LLMs Transcend Their Pretraining Origin?
  2. 2026Transformation-Augmented GRPO for Enhancing Exploration in Reasoning of Large Language Models
  3. 2025A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce
  4. 2025Explore Data Left Behind in Reinforcement Learning for Reasoning Language Models
  5. 2026Reason in the Words You Speak: Idiolectal Paraphrasing Off-Policy Traces for Reasoning Distillation in VideoLLMs
  6. 2026GRPO Beyond English: A Large-Scale Study of GRPO in Non-English and Multilingual Settings
  7. 2025GRPO-LEAD: A Difficulty-Aware Reinforcement Learning Approach for Concise Mathematical Reasoning in Language Models
  8. 2026AMIR-GRPO: Inducing Implicit Preference Signals into GRPO