mlsanityData to 14 Oct 2026

InternBootcamp: Boosting LLM Reasoning with Verifiable Task Scaling

arXiv 2508.08636 ↗First posted 12 Aug 2025cs.CLcited by 20

On the map: LLM reasoning → Reinforcement learning for reasoning

Abstract (arXiv)

Large language models (LLMs) have revolutionized artificial intelligence by enabling complex reasoning capabilities. While recent advancements in reinforcement learning (RL) have primarily focused on domain-specific reasoning tasks (e.g., mathematics or code generation), real-world reasoning scenarios often require models to handle diverse and complex environments that narrow-domain benchmarks cannot fully capture. To address this gap, we present InternBootcamp, an open-source framework comprising 1000+ domain-diverse task environments specifically designed for LLM reasoning research. With these bootcamps, we further establish Bootcamp-Eval, an automatically generated benchmark for comprehensive performance assessment. Evaluation reveals that frontier models still underperform in many reasoning tasks, while training with InternBootcamp provides an effective way to significantly improve performance, leading to our 32B model that achieves stateof-the-art results on Bootcamp-Eval and excels on other established benchmarks. In particular, we validate that consistent performance gain come from including more training tasks, namely task scaling, over two orders of magnitude, offering a promising route towards capable reasoning generalist. All data and code are publicly available.

Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Placed in Reinforcement learning for reasoning, one of 17 directions in LLM reasoning. Builds on 34 of its 57 references that are in the map. First posted on arXiv 12 Aug 2025.

Builds on

34 of 57 references.

Closest ancestors · 7

Same direction, newest first

  1. 2025SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond26 May
  2. 2025TTRL: Test-Time Reinforcement Learning22 Apr
  3. 2025Learning to Reason under Off-Policy Guidance21 Apr
  4. 2025VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks7 Apr
  5. 2025DAPO: An Open-Source LLM Reinforcement Learning System at Scale18 Mar
  6. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning22 Jan
  7. 2024AlphaMath Almost Zero: Process Supervision without Process6 May

Other references · 27

  1. 2025Qwen3 Technical Reportcited by 8,820
  2. 2020Measuring Massive Multitask Language Understandingcited by 7,963
  3. 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,371
  4. 2024Qwen2.5 Technical Reportcited by 4,942
  5. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,191
  6. 2024HybridFlow: A Flexible and Efficient RLHF Frameworkcited by 2,057
  7. 2024LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Codecited by 2,004
  8. 2024OpenAI o1 System Cardcited by 1,244
  9. 2023WizardLM: Empowering large pre-trained language models to follow complex instructionscited by 1,125
  10. 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discoverycited by 1,071
  11. 2024DeepSeek-V3 Technical Reportcited by 811
  12. 2023MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Modelscited by 735
15 more
  1. 2025Accelerating scientific discovery with Co-Scientistcited by 401
  2. 2025MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attentioncited by 263
  3. 2025ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoningcited by 201
  4. 2025Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyondcited by 175
  5. 2025Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learningcited by 161
  6. 2025BIG-Bench Extra Hardcited by 125
  7. 2025SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplinescited by 79
  8. 2024KOR-Bench: Benchmarking Language Models on Knowledge-Orthogonal Reasoning Taskscited by 70
  9. 2024Are Your LLMs Capable of Stable Reasoning?cited by 65
  10. 2024Puzzle Solving using Reasoning of Large Language Models: A Surveycited by 45
  11. 2025Game-RL: Synthesizing Multimodal Verifiable Game Data to Boost VLMs' General Reasoningcited by 32
  12. 2024Are Language Models Puzzle Prodigies? Algorithmic Puzzles Unveil Serious Challenges in Multimodal Reasoningcited by 25
  13. 2024GAMEBoT: Transparent Assessment of LLM Reasoning in Gamescited by 17
  14. 2025FastMCTS: A Simple Sampling Strategy for Data Synthesiscited by 17
  15. 2024FCoReBench: Can Large Language Models Solve Challenging First-Order Combinatorial Reasoning Problems?cited by 16

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 11; 2026: 9.

20 papers.

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By area:

  1. 2025The Landscape of Agentic Reinforcement Learning for LLMs: A Surveycited by 205
  2. 2025A Survey of Reinforcement Learning for Large Reasoning Modelscited by 180
  3. 2025Intern-S1: A Scientific Multimodal Foundation Modelcited by 53
  4. 2025RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environmentscited by 50
  5. 2025NP-Engine: Empowering Optimization Reasoning in Large Language Models with Verifiable Synthetic NP Problemscited by 11
  6. 2025A Survey of Inductive Reasoning for Large Language Modelscited by 8
  7. 2025Escaping the Verifier: Learning to Reason via Demonstrationscited by 7
  8. 2025Towards an AI Musician: Synthesizing Sheet Music Problems for Musical Reasoningcited by 6
  9. 2026Timely Machine: Awareness of Time Makes Test-Time Scaling Agenticcited by 6
  10. 2026Composition-RL: Compose Your Verifiable Prompts for Reinforcement Learning of Large Language Modelscited by 6
  11. 2025CP-Env: Evaluating Large Language Models on Clinical Pathways in a Controllable Hospital Environmentcited by 4
  12. 2026COSMO-Agent: Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestrationcited by 3
8 more
  1. 2025Code-driven Number Sequence Calculation: Enhancing the inductive Reasoning Abilities of Large Language Modelscited by 2
  2. 2026TL-GRPO: Turn-Level RL for Reasoning-Guided Iterative Optimizationcited by 1
  3. 2025MedCalc-Eval and MedCalc-Env: Advancing Medical Calculation Capabilities of Large Language Modelscited by 0
  4. 2026Forge: Quality-Aware Reinforcement Learning for NP-Hard Optimization in LLMscited by 0
  5. 2026Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestrationcited by 0
  6. 2026Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spacescited by 0
  7. 2026Entropy Pacing Policy Optimization for Multi-Task Agentic Reinforcement Learningcited by 0
  8. 2026Tev: Scaling Long-Horizon Agentic Environments with Dense Progress Rewardscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective
  2. 2025h1: Bootstrapping LLMs to Reason over Longer Horizons via Reinforcement Learning
  3. 2025DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training
  4. 2025General-Reasoner: Advancing LLM Reasoning Across All Domains
  5. 2025How Difficulty-Aware Staged Reinforcement Learning Enhances LLMs' Reasoning Capabilities: A Preliminary Experimental Study
  6. 2025VerifyBench: A Systematic Benchmark for Evaluating Reasoning Verifiers Across Domains
  7. 2025Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training
  8. 2025T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling