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# Who cites «STaR: Bootstrapping Reasoning With Reasoning» · page 5

585 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/zelikman-2022-star-bootstrapping-reasoning-reasoning/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/zelikman-2022-star-bootstrapping-reasoning-reasoning-2/) · [3](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/zelikman-2022-star-bootstrapping-reasoning-reasoning-3/) · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/zelikman-2022-star-bootstrapping-reasoning-reasoning-4/) · **5** · [6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/zelikman-2022-star-bootstrapping-reasoning-reasoning-6/)

1. [FOLIO: Natural Language Reasoning with First-Order Logic](https://arxiv.org/abs/2209.00840) *— 2022 · arXiv:2209.00840*
2. [Faithful Reasoning Using Large Language Models](https://arxiv.org/abs/2208.14271) *— 2022 · arXiv:2208.14271*
3. [Few-Shot Self-Rationalization with Natural Language Prompts](https://aclanthology.org/2022.findings-naacl.31/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
4. [Inferring Implicit Relations in Complex Questions with Language Models](https://aclanthology.org/2022.findings-emnlp.188/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
5. [Instruction Induction: From Few Examples to Natural Language Task Descriptions](https://arxiv.org/abs/2205.10782) *— 2022 · arXiv:2205.10782*
6. [Language Model Cascades](https://arxiv.org/abs/2207.10342) *— 2022 · arXiv:2207.10342*
7. [Language models show human-like content effects on reasoning tasks](https://arxiv.org/abs/2207.07051) *— 2022 · arXiv:2207.07051*
8. [Large Language Models Are Human-Level Prompt Engineers](https://arxiv.org/abs/2211.01910) *— 2022 · arXiv:2211.01910*
9. [Large language models are zero-shot reasoners](https://arxiv.org/abs/2205.11916) *— 2022*
10. [Learning by Distilling Context](https://arxiv.org/abs/2209.15189) *— 2022 · arXiv:2209.15189*
11. [Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models](https://aclanthology.org/2022.findings-emnlp.121/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
12. [Legal Prompting: Teaching a Language Model to Think Like a Lawyer](https://arxiv.org/abs/2212.01326) *— 2022 · arXiv:2212.01326*
13. [ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning](https://arxiv.org/abs/2212.07919) *— 2022 · arXiv:2212.07919*
14. [Rationale-Augmented Ensembles in Language Models](https://arxiv.org/abs/2207.00747) *— 2022 · arXiv:2207.00747*
15. [ReAct: Synergizing Reasoning and Acting in Language Models](https://arxiv.org/abs/2210.03629) *— 2022 · arXiv:2210.03629*
16. [Reasoning with Language Model Prompting: A Survey](https://arxiv.org/abs/2212.09597) *— 2022 · arXiv:2212.09597*
17. [Scaling Instruction-Finetuned Language Models](https://arxiv.org/abs/2210.11416) *— 2022 · arXiv:2210.11416*
18. [Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning](https://arxiv.org/abs/2205.09712) *— 2022 · arXiv:2205.09712*
19. [Solving math word problems with process- and outcome-based feedback](https://arxiv.org/abs/2211.14275) *— 2022 · arXiv:2211.14275*
20. [Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks](https://arxiv.org/abs/2204.02892) *— 2022 · arXiv:2204.02892*
21. [Successive Prompting for Decomposing Complex Questions](https://aclanthology.org/2022.emnlp-main.81/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
22. [Teaching Algorithmic Reasoning via In-context Learning](https://arxiv.org/abs/2211.09066) *— 2022 · arXiv:2211.09066*
23. acikgoz-2026-tt-si-self-improving-llm
24. ahn-2025-can-llms-deceive-clip-benchmarking
25. ai-2026-trajectory-learnability-offline-policy-distillation
26. akgul-2026-rethinking-rl-llm-reasoning-s
27. alrashed-2024-smoltulu-higher-learning-rate-batch
28. amin-2026-self-review-reinforcement-learning-srrl
29. bai-2026-k-opsd-verifiable-policy-self
30. balepur-2026-test-time-reasoners-are-strategic
31. barboni-2026-scaling-novel-graph-generation-lightweight
32. bostrom-2024-language-code-translation-single-labeled
33. bougie-2026-alignuser-human-aligned-llm-agents
34. bu-2025-enhanced-data-synthesis-llm-through
35. cai-2025-much-backtracking-enough-exploring-interplay
36. cano-2026-factcorrector-graph-inspired-approach-long
37. cao-2026-remedi-reasoner-medical-clinical-prediction
38. chen-2024-s3prompt-instructing-model-self-calibration
39. chen-2024-xplainllm-knowledge-augmented-dataset-reliable
40. chen-2026-rethinking-rl-evaluation-can-benchmarks
41. cho-2025-self-correcting-code-generation-small
42. chu-2024-navigate-through-enigmatic-labyrinth-survey
43. chung-2025-revisiting-test-time-scaling-survey
44. chungkham-2025-think-right-not-more-test
45. dai-2025-capture-key-reasoning-enhance-cot
46. dat-2026-dopsd-policy-self-distillation-diffusion
47. deng-2025-unlocking-reasoning-capabilities-llms-reinforcement
48. deng-2026-beyond-rejection-sampling-trajectory-fusion
49. deng-2026-data-centric-perspectives-agentic-retrieval
50. deng-2026-dgpo-beyond-pairwise-preferences-directional
51. deng-2026-weak-strong-elicitation-mismatched-wrong
52. ding-2026-empowering-multi-turn-tool-integrated
53. ding-2026-vista-verifier-informed-student-teacher
54. dixit-2026-ism-self-improving-strategy-memory
55. dong-2024-word-sense-disambiguation-as-game
56. dong-2026-gold-guided-programmatic-distillation-financial
57. du-2025-agentic-r1-distilled-dual-strategy
58. du-2026-powering-verifiable-learning-automated-evolutionary
59. dutt-2025-social-scaffolds-generalization-framework-social
60. erker-2026-grithopper-decomposition-free-multi-hop
61. fan-2023-chain-thought-tuning-masked-language
62. farazi-2025-troopers-blp-2025-task-2
63. feng-2026-formalize-once-edit-rest-efficient
64. gao-2025-marge-improving-math-reasoning-llms
65. gao-2026-thinking-economically-hierarchical-framework-adaptive
66. gourabathina-2026-answering-wrong-question-reasoning-trace
67. guo-2025-benchmarking-uncertainty-metrics-llm-target
68. guo-2026-counteracting-matthew-effect-self-improvement
69. haji-2025-reflective-agreement-combining-self-mixture
70. han-2024-context-learning-may-not-elicit
71. han-2025-long-short-llms-excel-trimming
72. hang-2025-scalable-complexity-control-facilitates-reasoning
73. he-2025-gentool-enhancing-tool-generalization-language
74. hebbar-2026-sia-self-improving-ai-harness
75. heddaya-2026-when-internalization-fails-finding-better
76. hossain-2026-overcoming-scaling-limits-policy-self
77. hu-2025-ltrag-enhancing-autoformalization-self-refinement
78. hu-2025-mllms-absorb-math-reasoning-abilities
79. ishibashi-2025-can-large-language-models-invent
80. ishibashi-2025-mining-hidden-thoughts-texts-evaluating
81. ishikawa-2025-idola-tribus-ai-large-language
82. jain-2025-undo-understanding-distillation-optimization
83. ji-2025-reflair-enhancing-multimodal-reasoning-structured
84. ji-2025-unlocking-llms-self-improvement-capacity
85. jiang-2026-immediate-inference-missing-foundation-large
86. jiang-2026-solvers-research-large-language-model
87. jung-2024-information-theoretic-distillation-reference-less
88. kachuee-2025-prismrag-boosting-rag-factuality-distractor
89. kadlcik-2024-self-training-language-models-arithmetic
90. karten-2026-prime-agent-self-improving-rlm
91. kato-2026-scaling-llm-reasoning-minimal-labels
92. khodadad-2026-evaluating-multi-hop-reasoning-large
93. kulshreshtha-2023-reasoning-circuits-few-shot-multi
94. lagzian-2026-mirage-multi-perspective-creative-language
95. lattimer-2025-sparse-rewards-can-self-train
96. le-2025-dp-ens-durationqa-dual-prompt
97. lee-2026-answer-conditioned-chains-thought-degrade
98. lee-2026-self-verified-distillation-language-model
99. li-2025-care-star-constraint-aware-self
100. li-2025-dice-structured-reasoning-llms-through

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