--- title: "Who cites Contrastive Chain-of-Thought — 38 citing papers" description: "38 papers of the Elamur Research library cite «Contrastive Chain-of-Thought Prompting», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/chia-2023-contrastive-chain-thought-prompting/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/chia-2023-contrastive-chain-thought-prompting/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Contrastive Chain-of-Thought Prompting](https://md.research.elamur.ai/free/en/papers/chia-2023-contrastive-chain-thought-prompting/) / cited by # Who cites «Contrastive Chain-of-Thought Prompting» 38 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «Contrastive Chain-of-Thought Prompting»](https://md.research.elamur.ai/free/en/papers/chia-2023-contrastive-chain-thought-prompting/) 1. [**A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications arXiv:2402.07927**Pranab Sahoo; Ayush Kumar Singh; Sriparna Saha; Vinija Jain; Samrat Mondal;, Aman Chadha*2024 · 375 citations*](https://md.research.elamur.ai/free/en/papers/sahoo-2024-systematic-survey-prompt-engineering-large/) 2. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/) 3. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/) 4. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/) 5. [**Reasoning Models Don't Always Say What They Think arXiv:2505.05410**Yanda Chen, Joe Benton, Ansh Radhakrishnan, et al.*2025 · 106 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-reasoning-models-don-t-always/) 6. **[Recursive Introspection: Teaching Language Model Agents How to Self-Improve](https://md.research.elamur.ai/free/en/papers/qu-2024-recursive-introspection-teaching-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiao Qu, Tianjun Zhang, Naman Garg, et al.*2024 · 75 citations* 7. [**In-Context Principle Learning from Mistakes arXiv:2402.05403**Tianjun Zhang, Aman Madaan, Luyu Gao, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-context-principle-learning-mistakes/) 8. [**Distillation Contrastive Decoding: Improving LLMs Reasoning with Contrastive Decoding and Distillation arXiv:2402.14874**Phuc Phan, Hieu Tran, Long Phan*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/phan-2024-distillation-contrastive-decoding-improving-llms/) 9. [**Baichuan Alignment Technical Report arXiv:2410.14940**Mingan Lin, Fan Yang, Yanjun Shen, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-baichuan-alignment-technical-report/) 10. **[AILS-NTUA at SemEval-2026 Task 10: Agentic LLMs for Psycholinguistic Marker Extraction and Conspiracy Endorsement Detection](https://md.research.elamur.ai/free/en/papers/spanakis-2026-ails-ntua-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Panagiotis Spanakis, Maria Lymperaiou, Giorgos Filandrianos, et al.*2026 · 2 citations* 11. **[How Chain-of-Thought Works? Tracing Information Flow from Decoding, Projection, and Activation](https://md.research.elamur.ai/free/en/papers/yang-2026-how-chain-thought-works-tracing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Yang, Qinghua Zhao, Lei Li, et al.*2026 · 1 citation* 27 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/chia-2023-contrastive-chain-thought-prompting/) — Contrastive Chain-of-Thought Prompting