--- title: "Who cites Vyas Raina — 67 papers of our library" description: "67 papers of the Elamur Research library cite the works of Vyas Raina, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/vyas-raina/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/vyas-raina/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Vyas Raina](https://md.research.elamur.ai/free/en/authors/vyas-raina/) / cited by # Who cites Vyas Raina 67 citations of their works from 67 papers of our library (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← Vyas Raina](https://md.research.elamur.ai/free/en/authors/vyas-raina/) 1. **[s1: Simple test-time scaling](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.*2025 · 608 citations* 2. [**Large Language Monkeys: Scaling Inference Compute with Repeated Sampling arXiv:2407.21787**Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.*2024 · 270 citations*](https://md.research.elamur.ai/free/en/papers/brown-2024-large-language-monkeys-scaling-inference/) 3. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/) 4. **[Humans or LLMs as the Judge? A Study on Judgement Bias](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-or-llms-as-judge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 133 citations* 5. [**Humans or LLMs as the Judge? A Study on Judgement Biases arXiv:2402.10669**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-llms-judge-study-judgement/) 6. **[Judging the Judges: A Systematic Study of Position Bias in LLM-as-a-Judge](https://md.research.elamur.ai/free/en/papers/shi-2025-judging-judges-systematic-study-position/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Lin Shi, Chiyu Ma, Wenhua Liang, et al.*2025 · 71 citations* 7. **[CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges](https://md.research.elamur.ai/free/en/papers/li-2025-calibraeval-calibrating-prediction-distribution-mitigate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haitao Li, Junjie Chen, Qingyao Ai, et al.*2025 · 15 citations* 8. **[Understanding Figurative Meaning through Explainable Visual Entailment](https://md.research.elamur.ai/free/en/papers/saakyan-2025-understanding-figurative-meaning-through-explainable/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Arkadiy Saakyan, Shreyas Kulkarni, Tuhin Chakrabarty, et al.*2025 · 15 citations* 9. **[Safer or Luckier? LLMs as Safety Evaluators Are Not Robust to Artifacts](https://md.research.elamur.ai/free/en/papers/chen-2025-safer-or-luckier-llms-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongyu Chen, Seraphina Goldfarb-Tarrant*2025 · 13 citations* 10. [**From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks arXiv:2409.04168**Andreas Stephan, Dawei Zhu, Matthias Aßenmacher, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/stephan-2024-calculation-adjudication-examining-llm-judges/) 11. **[UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision](https://md.research.elamur.ai/free/en/papers/fang-2026-unicorn-self-improving-unified-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Fang, Ruiyan Han, XinYu Sun, et al.*2026 · 11 citations* 12. **[Can LLMs Really Judge? A Progressive Argumentation-Mining Framework for Distinguishing Understanding from Aggregation](https://md.research.elamur.ai/free/en/papers/wang-2026-can-llms-really-judge-progressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fuyu Wang, Jiangtong Li, Kun Zhu, et al.*2026* 13. **[Learning to Refine: Self-Refinement of Parallel Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-refine-self-refinement-parallel/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qibin Wang, Pu Zhao, Shaohan Huang, et al.*2026* 14. **[Reasoning Hijacking: The Fragility of Reasoning Alignment in Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2026-reasoning-hijacking-fragility-reasoning-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuansen Liu, Yixuan Tang, Anthony Kum Hoe Tung*2026* 15. **[Self-Consistency from Only Two Samples: CoT–PoT Ensembling for Efficient LLM Reasoning](https://md.research.elamur.ai/free/en/papers/saparkhan-2026-self-consistency-only-two-samples/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Raman Saparkhan, Majd Hawasly, Md Rizwan Parvez, et al.*2026* 52 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/vyas-raina/) — Vyas Raina