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home / docs / papers / cited-by / Who cites «STaR: Bootstrapping Reasoning With Reasoning» · page 3

Who cites «STaR: Bootstrapping Reasoning With Reasoning» · page 3

585 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

Pages: 1 · 2 · 3 · 4 · 5 · 6

  1. DataComp-LM: In search of the next generation of training sets for language models — 2024 · arXiv:2406.11794
  2. Dialogue Ontology Relation Extraction via Constrained Chain-of-Thought Decoding — 2024 · Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue
  3. Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs — 2024 · arXiv:2412.21187
  4. Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces — 2024 · arXiv:2410.09918
  5. DynaThink: Fast or Slow? A Dynamic Decision-Making Framework for Large Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  6. ELAD: Explanation-Guided Large Language Models Active Distillation — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  7. Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision — 2024 · arXiv:2403.09472
  8. EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)
  9. Enhancing Chain-of-Thoughts Prompting with Iterative Bootstrapping in Large Language Models — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  10. FOLIO: Natural Language Reasoning with First-Order Logic — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  11. Feedback Loops With Language Models Drive In-Context Reward Hacking — 2024 · arXiv:2402.06627
  12. Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  13. Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  14. From $r$ to $Q^*$: Your Language Model is Secretly a Q-Function — 2024 · arXiv:2404.12358
  15. GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents — 2024 · arXiv:2406.06613
  16. Generating Mental Health Transcripts with SAPE (Spanish Adaptive Prompt Engineering) — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  17. Generative Reward Models — 2024 · arXiv:2410.12832
  18. Generative Verifiers: Reward Modeling as Next-Token Prediction — 2024 · arXiv:2408.15240
  19. Grokked Transformers are Implicit Reasoners: A Mechanistic Journey to the Edge of Generalization — 2024 · arXiv:2405.15071
  20. HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs — 2024 · arXiv:2412.18925
  21. I Learn Better If You Speak My Language: Understanding the Superior Performance of Fine-Tuning Large Language Models with LLM-Generated Responses — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  22. Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning Systems — 2024 · arXiv:2412.09413
  23. Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  24. Improving Language Model Reasoning with Self-motivated Learning — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  25. Improving Large Language Models in Event Relation Logical Prediction — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  26. In-Context Learning with Iterative Demonstration Selection — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  27. In-Context Principle Learning from Mistakes — 2024 · arXiv:2402.05403
  28. InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning — 2024 · arXiv:2402.06332
  29. Interpreting and Improving Large Language Models in Arithmetic Calculation — 2024 · arXiv:2409.01659
  30. Iterative Reasoning Preference Optimization — 2024 · arXiv:2404.19733
  31. LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  32. LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  33. LMEME at SemEval-2024 Task 4: Teacher Student Fusion - Integrating CLIP with LLMs for Enhanced Persuasion Detection — 2024 · Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
  34. Lean-STaR: Learning to Interleave Thinking and Proving — 2024 · arXiv:2407.10040
  35. Learning Formal Mathematics From Intrinsic Motivation — 2024 · arXiv:2407.00695
  36. Learning to Ask Informative Questions: Enhancing LLMs with Preference Optimization and Expected Information Gain — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  37. Learning to Correct for QA Reasoning with Black-box LLMs — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  38. Leveraging Machine-Generated Rationales to Facilitate Social Meaning Detection in Conversations — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  39. M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  40. Masked Thought: Simply Masking Partial Reasoning Steps Can Improve Mathematical Reasoning Learning of Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  41. Mastering Board Games by External and Internal Planning with Language Models — 2024 · arXiv:2412.12119
  42. Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding — 2024 · arXiv:2401.12954
  43. Mirror: Multiple-perspective Self-Reflection Method for Knowledge-rich Reasoning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  44. MoDE-CoTD: Chain-of-Thought Distillation for Complex Reasoning Tasks with Mixture of Decoupled LoRA-Experts — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  45. Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning — 2024 · arXiv:2405.00451
  46. MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  47. NExT: Teaching Large Language Models to Reason about Code Execution — 2024 · arXiv:2404.14662
  48. O1 Replication Journey -- Part 2: Surpassing O1-preview through Simple Distillation, Big Progress or Bitter Lesson? — 2024 · arXiv:2411.16489
  49. O1 Replication Journey: A Strategic Progress Report -- Part 1 — 2024 · arXiv:2410.18982
  50. On the Diversity of Synthetic Data and its Impact on Training Large Language Models — 2024 · arXiv:2410.15226
  51. OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset — 2024 · arXiv:2402.10176
  52. OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models — 2024 · arXiv:2410.09671
  53. P-FOLIO: Evaluating and Improving Logical Reasoning with Abundant Human-Written Reasoning Chains — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  54. Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security — 2024 · arXiv:2401.05459
  55. Planning In Natural Language Improves LLM Search For Code Generation — 2024 · arXiv:2409.03733
  56. Preference Optimization for Reasoning with Pseudo Feedback — 2024 · arXiv:2411.16345
  57. Progress or Regress? Self-Improvement Reversal in Post-training — 2024 · arXiv:2407.05013
  58. Prompt Engineering a Prompt Engineer — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  59. Quiet-STaR: Language models can teach themselves to think before speaking — 2024
  60. RAG-HAT: A Hallucination-Aware Tuning Pipeline for LLM in Retrieval-Augmented Generation — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track
  61. RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation — 2024 · arXiv:2403.05313
  62. RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold — 2024 · arXiv:2406.14532
  63. RankPrompt: Step-by-Step Comparisons Make Language Models Better Reasoners — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  64. Re-ReST: Reflection-Reinforced Self-Training for Language Agents — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  65. ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  66. ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search — 2024 · arXiv:2406.03816
  67. Recursive Introspection: Teaching Language Model Agents How to Self-Improve — 2024 · arXiv:2407.18219
  68. Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key? — 2024 · arXiv:2402.18272
  69. Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning — 2024 · arXiv:2410.08146
  70. SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models — 2024 · arXiv:2408.15565
  71. STaR-GATE: Teaching Language Models to Ask Clarifying Questions — 2024 · arXiv:2403.19154
  72. Scalable Reinforcement Post-Training Beyond Static Human Prompts: Evolving Alignment via Asymmetric Self-Play — 2024 · arXiv:2411.00062
  73. Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters — 2024 · arXiv:2408.03314
  74. Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective — 2024 · arXiv:2412.14135
  75. SeRTS: Self-Rewarding Tree Search for Biomedical Retrieval-Augmented Generation — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  76. Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering — 2024 · arXiv:2411.11504
  77. Self-Data Distillation for Recovering Quality in Pruned Large Language Models — 2024 · arXiv:2410.09982
  78. Self-Explore: Enhancing Mathematical Reasoning in Language Models with Fine-grained Rewards — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  79. Self-Improvement in Language Models: The Sharpening Mechanism — 2024 · arXiv:2412.01951
  80. Self-Refine Instruction-Tuning for Aligning Reasoning in Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  81. Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels — 2024 · arXiv:2404.14313
  82. Self-Training with Direct Preference Optimization Improves Chain-of-Thought Reasoning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  83. Small Language Models Need Strong Verifiers to Self-Correct Reasoning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  84. Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling — 2024 · arXiv:2408.16737
  85. SocREval: Large Language Models with the Socratic Method for Reference-free Reasoning Evaluation — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  86. StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows — 2024 · arXiv:2403.11322
  87. Stream of Search (SoS): Learning to Search in Language — 2024 · arXiv:2404.03683
  88. TangoFlux: Super Fast and Faithful Text to Audio Generation with Flow Matching and Clap-Ranked Preference Optimization — 2024 · arXiv:2412.21037
  89. Teaching Large Language Models to Reason with Reinforcement Learning — 2024 · arXiv:2403.04642
  90. TextGrad: Automatic "Differentiation" via Text — 2024 · arXiv:2406.07496
  91. The Llama 3 Herd of Models — 2024 · arXiv:2407.21783
  92. The pitfalls of next-token prediction — 2024 · arXiv:2403.06963
  93. Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing — 2024 · arXiv:2404.12253
  94. Training Language Models to Self-Correct via Reinforcement Learning — 2024 · arXiv:2409.12917
  95. Tulu 3: Pushing Frontiers in Open Language Model Post-Training — 2024 · arXiv:2411.15124
  96. V-STaR: Training Verifiers for Self-Taught Reasoners — 2024 · arXiv:2402.06457
  97. Weak-to-Strong Reasoning — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  98. Weak-to-Strong Search: Align Large Language Models via Searching over Small Language Models — 2024 · arXiv:2405.19262
  99. When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs — 2024 · Transactions of the Association for Computational Linguistics
  100. mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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