---
title: "Who cites Kundan Krishna — 138 papers of our library"
description: "138 papers of the Elamur Research library cite the works of Kundan Krishna, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/kundan-krishna/cited-by/"
---
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# Who cites Kundan Krishna

138 citations of their works from 138 papers of our library (of the 149,439 whose bibliographies we read) · 26 with a page here, the most cited first · [← Kundan Krishna](https://md.research.elamur.ai/free/en/authors/kundan-krishna/)

1. [**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/)
2. **[SummScreen: A Dataset for Abstractive Screenplay Summarization](https://md.research.elamur.ai/free/en/papers/chen-2022-summscreen-dataset-abstractive-screenplay-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingda Chen, Zewei Chu, Sam Wiseman, et al.*2022 · 136 citations*
3. [**INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection arXiv:2402.03744**Chao Chen, Kai Liu, Ze Chen, et al.*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-inside-llms-internal-states-retain/)
4. [**A Survey of Confidence Estimation and Calibration in Large Language Models arXiv:2311.08298**Jiahui Geng, Fengyu Cai, Yuxia Wang, et al.*2023 · 97 citations*](https://md.research.elamur.ai/free/en/papers/geng-2023-survey-confidence-estimation-calibration-large/)
5. **[Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification](https://md.research.elamur.ai/free/en/papers/fadeeva-2024-fact-checking-output-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, et al.*2024 · 96 citations*
6. **[Selectively Answering Ambiguous Questions](https://md.research.elamur.ai/free/en/papers/cole-2023-selectively-answering-ambiguous-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jeremy Cole, Michael Zhang, Daniel Gillick, et al.*2023 · 84 citations*
7. [**Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer**Eleftheria Briakou, Sweta Agrawal, Joel Tetreault, et al.*2021 · 49 citations*](https://md.research.elamur.ai/free/en/papers/briakou-2021-evaluating-evaluation-metrics-style-transfer/)
8. **[Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home](https://md.research.elamur.ai/free/en/papers/moskvoretskii-2025-adaptive-retrieval-without-self-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Viktor Moskvoretskii, Maria Marina, Mikhail Salnikov, et al.*2025 · 21 citations*
9. **[ICR Probe: Tracking Hidden State Dynamics for Reliable Hallucination Detection in LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-icr-probe-tracking-hidden-state/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenliang Zhang, Xinyu Hu, Huixuan Zhang, et al.*2025 · 14 citations*
10. **[MediTOD: An English Dialogue Dataset for Medical History Taking with Comprehensive Annotations](https://md.research.elamur.ai/free/en/papers/saley-2024-meditod-english-dialogue-dataset-medical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Vishal Vivek Saley, Goonjan Saha, Rocktim Jyoti Das, et al.*2024 · 14 citations*
11. **[Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-token-level-density-based-uncertainty/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, et al.*2025 · 13 citations*
12. **[Synthetic Arabic Medical Dialogues Using Advanced Multi-Agent LLM Techniques](https://md.research.elamur.ai/free/en/papers/almutairi-2024-synthetic-arabic-medical-dialogues-advanced/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Mariam ALMutairi, Lulwah AlKulaib, Melike Aktas, et al.*2024 · 12 citations*
13. **[Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering](https://md.research.elamur.ai/free/en/papers/si-2025-aligning-large-language-models-follow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuzheng Si, Haozhe Zhao, Gang Chen, et al.*2025 · 11 citations*
14. **[Is That Your Final Answer? Test-Time Scaling Improves Selective Question Answering](https://md.research.elamur.ai/free/en/papers/jurayj-2025-is-that-your-final-answer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**William Jurayj, Jeffrey Cheng, Benjamin Van Durme*2025 · 11 citations*
15. **[Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-unconditional-truthfulness-learning-unconditional-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.*2025 · 10 citations*
16. **[MUR: Momentum Uncertainty guided Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-mur-momentum-uncertainty-guided-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hang Yan, Fangzhi Xu, Rongman Xu, et al.*2026 · 8 citations*
17. **[Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?](https://md.research.elamur.ai/free/en/papers/yan-2025-recitation-over-reasoning-how-cutting/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Kai Yan, Yufei Xu, Zhengyin Du, et al.*2025 · 5 citations*
18. **[Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changdae Oh, Seongheon Park, To Eun Kim, et al.*2026 · 4 citations*
19. **[Constructing a Dataset for Hallucination Detection in Japanese Summarization with Fine-grained Faithfulness Labels](https://md.research.elamur.ai/free/en/papers/tanaka-2026-constructing-dataset-hallucination-detection-japanese/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hikari Tanaka, Atsushi Keyaki, Mamoru Komachi*2026*
20. **[FU-HU-P5 at #SMM4H-HeaRD 2026: MedSynth Dialogue-to-Note Generation](https://md.research.elamur.ai/free/en/papers/wong-2026-fu-hu-p5-smm4h-heard/) [Social Media Mining for Health Research and Applications Workshop and Shared Tasks](https://md.research.elamur.ai/free/en/venues/smm4h/)**Jessica Ying En Wong*2026*
21. **[LatentRefusal: Latent-Signal Refusal for Unanswerable Text-to-SQL Queries](https://md.research.elamur.ai/free/en/papers/ren-2026-latentrefusal-latent-signal-refusal-unanswerable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuancheng Ren, Shijing Hu, Zhihui Lu, et al.*2026*
22. **[Learning Uncertainty from Sequential Internal Dispersion in Large Language Models](https://md.research.elamur.ai/free/en/papers/srey-2026-learning-uncertainty-sequential-internal-dispersion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.*2026*
23. **[NU_DeepHealthNLP at #SMM4H-HeaRD 2026: Entity-Conditioned Generation and a Four-Stage Pipeline for Automated SOAP Note Generation](https://md.research.elamur.ai/free/en/papers/santhosh-2026-nu-deephealthnlp-smm4h-heard-2026/) [Social Media Mining for Health Research and Applications Workshop and Shared Tasks](https://md.research.elamur.ai/free/en/venues/smm4h/)**Thanya Mysore Santhosh, Deahan Yu*2026*
24. **[RFS-Guard: Detecting Reasoning Hallucinations via Cross-Phase Routing Focus in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-rfs-guard-detecting-reasoning-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihang Liu, Fang Zhouhua, Hui Liu, et al.*2026*
25. **[TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG](https://md.research.elamur.ai/free/en/papers/lu-2026-tpa-next-token-probability-attribution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengqian Lu, Jie Lu, Anjin Liu, et al.*2026*
26. **[VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation](https://md.research.elamur.ai/free/en/papers/park-2026-vauq-vision-aware-uncertainty-quantification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seongheon Park, Changdae Oh, Hyeong Kyu Choi, et al.*2026*

112 more citing papers of our library have no page here yet.

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