---
title: "Who cites Pawan Goyal — 417 papers of our library"
description: "417 papers of the Elamur Research library cite the works of Pawan Goyal, found in their bibliographies; the most cited first."
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---
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# Who cites Pawan Goyal

431 citations of their works from 417 papers of our library (of the 149,439 whose bibliographies we read) · 52 with a page here, the most cited first · [← Pawan Goyal](https://md.research.elamur.ai/free/en/authors/pawan-goyal/)

1. **[Explainability for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhao-2023-explainability-large-language-models-survey/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Haiyan Zhao, Hanjie Chen, Fan Yang, et al.*2023 · 790 citations*
2. [**LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models arXiv:2308.11462**Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Re; Adam Chilton; Aditya Narayana; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; Enam Hoque; Faiz Surani; Frank Fagan; Galit Sarfaty; Gregory M. Dickinson; Haggai Porat; Jason Hegland; Jessica Wu; Joe Nudell; Joel Niklaus; John Nay; Jonathan H. Choi; Kevin Tobia; Margaret Hagan; Megan Ma; Michael Livermore; Nikon Rasumov-Rahe; Nils Holzenberger; Noam Kolt; Peter Henderson; Sean Rehaag; Sharad Goel; Shang Gao; Spencer Williams; Sunny Gandhi; Tom Zur; Varun Iyer;, Zehua Li*2023 · 389 citations*](https://md.research.elamur.ai/free/en/papers/guha-2023-legalbench-collaboratively-built-benchmark-measuring/)
3. **[Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection](https://md.research.elamur.ai/free/en/papers/vidgen-2021-learning-worst-dynamically-generated-datasets/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bertie Vidgen, Tristan Thrush, Zeerak Waseem, et al.*2021 · 325 citations*
4. **[From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models](https://md.research.elamur.ai/free/en/papers/feng-2023-pretraining-data-language-models-downstream/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Chan Young Park, Yuhan Liu, et al.*2023 · 311 citations*
5. **[SemEval-2023 Task 10: Explainable Detection of Online Sexism](https://md.research.elamur.ai/free/en/papers/kirk-2023-semeval-2023-task-10-explainable/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Hannah Kirk, Wenjie Yin, Bertie Vidgen, et al.*2023 · 185 citations*
6. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
7. **[Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/louis-2023-interpretable-long-form-legal-question/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Antoine Louis, Gijs van Dijck, Gerasimos Spanakis*2023 · 157 citations*
8. **[Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech](https://md.research.elamur.ai/free/en/papers/fanton-2021-human-loop-data-collection-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Margherita Fanton, Helena Bonaldi, Serra Sinem Tekiroğlu, et al.*2021 · 118 citations*
9. **[On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations](https://md.research.elamur.ai/free/en/papers/cao-2022-intrinsic-extrinsic-fairness-evaluation-metrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, et al.*2022 · 100 citations*
10. **[POLAR: A Benchmark for Multilingual, Multicultural, and Multi-Event Online Polarization](https://md.research.elamur.ai/free/en/papers/naseem-2026-polar-benchmark-multilingual-multicultural-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Usman Naseem, Robert Geislinger, Juan Ren, et al.*2026 · 61 citations*
11. **[SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization](https://md.research.elamur.ai/free/en/papers/naseem-2026-semeval-2026-task-9-detecting/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Usman Naseem, Robert Geislinger, Ada Ren, et al.*2026 · 61 citations*
12. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
13. [**One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support arXiv:2306.09237**Ronja Stern, Vishvaksenan Rasiah, Veton Matoshi, et al.*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/stern-2023-one-law-many-languages-benchmarking/)
14. **[Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models](https://md.research.elamur.ai/free/en/papers/kim-2024-developing-pragmatic-benchmark-assessing-korean/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yeeun Kim, Youngrok Choi, Eunkyung Choi, et al.*2024 · 24 citations*
15. **[Multilingual and Explainable Text Detoxification with Parallel Corpora](https://md.research.elamur.ai/free/en/papers/dementieva-2025-multilingual-explainable-text-detoxification-parallel/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Daryna Dementieva, Nikolay Babakov, Amit Ronen, et al.*2025 · 19 citations*
16. [**Exploring Transformer Based Models to Identify Hate Speech and Offensive Content in English and Indo-Aryan Languages arXiv:2111.13974**Somnath Banerjee, Maulindu Sarkar, Nancy Agrawal, et al.*2021 · 17 citations*](https://md.research.elamur.ai/free/en/papers/banerjee-2021-exploring-transformer-based-models-identify/)
17. **[LexSumm and LexT5: Benchmarking and Modeling Legal Summarization Tasks in English](https://md.research.elamur.ai/free/en/papers/s-2024-lexsumm-lext5-benchmarking-modeling-legal/) [Natural Legal Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/nllp/)**Santosh T.Y.S.S, Cornelius Weiss, Matthias Grabmair*2024 · 16 citations*
18. **[Exploring Amharic Hate Speech Data Collection and Classification Approaches](https://md.research.elamur.ai/free/en/papers/ayele-2023-exploring-amharic-hate-speech-data/) [Recent Advances in Natural Language Processing (RANLP)](https://md.research.elamur.ai/free/en/venues/ranlp/)**Abinew Ali Ayele, Seid Muhie Yimam, Tadesse Destaw Belay, et al.*2023 · 12 citations*
19. **[Can LLMs Evaluate What They Cannot Annotate? Revisiting LLM Reliability in Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/piot-2026-can-llms-evaluate-what-they/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paloma Piot, David Otero, Patricia Martin-Rodilla, et al.*2026 · 5 citations*
20. **[A Survey of Machine Learning Models and Datasets for the Multi-label Classification of Textual Hate Speech in English](https://md.research.elamur.ai/free/en/papers/baumler-2025-survey-machine-learning-models-datasets/) [ACM Transactions on Knowledge Discovery from Data](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-knowledge-discovery-from-data/)**Julian Baumler, Louis Blocher, Lars-Joel Frey, et al.*2025 · 4 citations*
21. **[Detecting Hate Speech in Amharic Using Multimodal Analysis of Social Media Memes](https://md.research.elamur.ai/free/en/papers/jigar-2024-detecting-hate-speech-amharic-multimodal/) [Workshop on Trolling, Aggression and Cyberbullying](https://md.research.elamur.ai/free/en/venues/trac/)**Melese Ayichlie Jigar, Abinew Ali Ayele, Seid Muhie Yimam, et al.*2024 · 4 citations*
22. [**Toxic language detection: a systematic review of Arabic datasets arXiv:2312.07228**Imene Bensalem, Paolo Rosso, Hanane Zitouni*2023 · 4 citations*](https://md.research.elamur.ai/free/en/papers/bensalem-2023-toxic-language-detection-systematic-review/)
23. **[A Survey on Combating Hate Speech through Detection and Prevention in English](https://md.research.elamur.ai/free/en/papers/kapil-2024-survey-combating-hate-speech-through/) [International Conference on Natural Language Processing (ICON)](https://md.research.elamur.ai/free/en/venues/icon/)**Prashant Kapil, Asif Ekbal*2024 · 3 citations*
24. **[Argument-Based Consistency in Toxicity Explanations of LLMs](https://md.research.elamur.ai/free/en/papers/mothilal-2026-argument-based-consistency-toxicity-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ramaravind Kommiya Mothilal, Joanna Roy, Syed Ishtiaque Ahmed, et al.*2026 · 2 citations*
25. **[Persona Prompting as a Lens on LLM Social Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2026-persona-prompting-as-lens-llm/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jing Yang, Moritz Hechtbauer, Elisabeth Khalilov, et al.*2026 · 2 citations*
26. **[Self-Explaining Hate Speech Detection with Moral Rationales](https://md.research.elamur.ai/free/en/papers/vargas-2026-self-explaining-hate-speech-detection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Francielle Vargas, Jackson Trager, Diego Alves, et al.*2026 · 2 citations*
27. **[Can Contextualizing User Embeddings Improve Sarcasm and Hate Speech Detection?](https://md.research.elamur.ai/free/en/papers/breitwieser-2022-can-contextualizing-user-embeddings-improve/) [Workshop on Natural Language Processing and Computational Social Science](https://md.research.elamur.ai/free/en/venues/nlpcss/)**Kim Breitwieser*2022 · 2 citations*
28. **[Aatman at SemEval-2026 Task 9: Transfer Learning for Multilingual Polarization Detection](https://md.research.elamur.ai/free/en/papers/vaidya-2026-aatman-semeval-2026-task-9/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Aatman Vaidya*2026 · 1 citation*
29. **[Antisocial Behavior Prediction: A Survey and Practical Guide](https://md.research.elamur.ai/free/en/papers/ollagnier-2026-antisocial-behavior-prediction-survey-practical/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Anaïs Ollagnier*2026 · 1 citation*
30. **[HARM: Learning Hate-Aware Reward Model for Evaluating Natural Language Explanations of Offensive Content](https://md.research.elamur.ai/free/en/papers/vecchi-2026-harm-learning-hate-aware-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lorenzo Puppi Vecchi, Alceu de Souza Britto Jr, Emerson Cabrera Paraiso, et al.*2026 · 1 citation*
31. **[SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Models](https://md.research.elamur.ai/free/en/papers/nghiem-2026-smarter-data-efficient-framework-improve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huy Nghiem, Advik Sachdeva, Hal Daumé Iii*2026 · 1 citation*
32. **[STEM TOX: From Collaborative Tags to Fine-Grained Toxic Meme Detection via Entropy-Guided Multi-Task Learning](https://md.research.elamur.ai/free/en/papers/swain-2026-stem-tox-collaborative-tags-fine/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Subhankar Swain, Naquee Rizwan, Vishwa Gangadhar S, et al.*2026 · 1 citation*
33. **[How Much Do Robots Understand Rudeness? Challenges in Human-Robot Interaction](https://md.research.elamur.ai/free/en/papers/orme-2024-how-much-do-robots-understand/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Michael Andrew Orme, Yanchao Yu, Zhiyuan Tan*2024 · 1 citation*
34. **[OLEA: Tool and Infrastructure for Offensive Language Error Analysis in English](https://md.research.elamur.ai/free/en/papers/grace-2023-olea-tool-infrastructure-offensive-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Marie Grace, Jay Seabrum, Dananjay Srinivas, et al.*2023 · 1 citation*
35. [**Overview of the HASOC Subtrack at FIRE 2023: Identification of Tokens Contributing to Explicit Hate in English by Span Detection arXiv:2311.09834**Sarah Masud, Mohammad Aflah Khan, Md. Shad Akhtar, et al.*2023 · 1 citation*](https://md.research.elamur.ai/free/en/papers/masud-2023-overview-hasoc-subtrack-fire-2023/)
36. **[A Position Paper on Toxic Reasoning: Grounding Categories of Toxic Language in Implications and Attitudes](https://md.research.elamur.ai/free/en/papers/schouten-2026-position-paper-toxic-reasoning-grounding/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Stefan F. Schouten, Ilia Markov, Piek Vossen*2026*
37. **[AYN: A Tiny Yet Competitive Indian Legal Language Model Pretrained from Scratch](https://md.research.elamur.ai/free/en/papers/niyogi-2026-ayn-tiny-yet-competitive-indian/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya*2026*
38. **[BanHADEX: Towards Explainable HAte Speech Detection in Bangla Using Human Annotated EXplanation](https://md.research.elamur.ai/free/en/papers/raquib-2026-banhadex-explainable-hate-speech-detection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Faisal Hossain Raquib, Akm Moshiur Rahman Mazumder, Md Fahim, et al.*2026*
39. **[Danger Depends on the Mind: A Theory-of-Mind Grounded Dataset and Model for Context-Dependent Dangerous Speech](https://md.research.elamur.ai/free/en/papers/shi-2026-danger-depends-mind-theory-mind/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanchen Shi, Longyin Zhang, Guodong Zhou, et al.*2026*
40. **[Evaluating LLMs for Detecting Demographic-Targeted Social Bias: A Comprehensive Benchmark Study](https://md.research.elamur.ai/free/en/papers/majumdar-2026-evaluating-llms-detecting-demographic-targeted/) [Workshop of Identity Aware AI](https://md.research.elamur.ai/free/en/venues/iaai/)**Ayan Majumdar, Feihao Chen, Jinghui Li, et al.*2026*
41. **[HatePrototypes: Interpretable and Transferable Representations for Implicit and Explicit Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/proskurina-2026-hateprototypes-interpretable-transferable-representations-implicit/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Irina Proskurina, Marc-Antoine Carpentier, Julien Velcin*2026*
42. **[ILSIC: Corpora for Identifying Indian Legal Statutes from Queries by Laymen](https://md.research.elamur.ai/free/en/papers/paul-2026-ilsic-corpora-identifying-indian-legal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shounak Paul, Raghav Dogra, Pawan Goyal, et al.*2026*
43. **[Leveraging Semi-Supervised Learning for Multimodal Hate Speech Data Annotation and Detection](https://md.research.elamur.ai/free/en/papers/rammohan-2026-leveraging-semi-supervised-learning-multimodal/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rathi Adarshi Rammohan, Zhao Ren, Dominik Puchała, et al.*2026*
44. **[Penetrating Linguistic Disguises: A Slang-aware Label-Aligned Framework for Fine-Grained Toxicity Extraction in Chinese Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/liu-2026-penetrating-linguistic-disguises-slang-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wei Liu, Xiaoliang Chen, Duoqian Miao, et al.*2026*
45. [**ProBel: Propaganda Detection with Techniques, Spans, and Explanations arXiv:2608.22388**Mohamed Bayan Kmainasi, Ali Ezzat Shahroor, Elisa Sartori, et al.*2026*](https://md.research.elamur.ai/free/en/papers/kmainasi-2026-probel-propaganda-detection-techniques-spans/)
46. **[Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej](https://md.research.elamur.ai/free/en/papers/nigam-2026-structured-legal-document-generation-india/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Shubham Kumar Nigam, Deepak Patnaik Balaramamahanthi, Noel Shallum, et al.*2026*
47. **[TAGA@EEUCA 2026: Token-Attribution Guided Attention for Fine-Grained Toxic Behaviour Classification in Online Gaming Communities](https://md.research.elamur.ai/free/en/papers/shah-2026-taga-eeuca-2026-token-attribution/) [Workshop on Event Extraction and Understanding: Challenges and Applications](https://md.research.elamur.ai/free/en/venues/eeuca/)**Akshyat Shah, Shashi Sah, Aryan Gupta, et al.*2026*
48. **[wangkongqiang@EEUCA 2026: Understanding Toxic Behavioral Intent in Gaming Chat Logs](https://md.research.elamur.ai/free/en/papers/wang-2026-wangkongqiang-eeuca-2026-understanding-toxic/) [Workshop on Event Extraction and Understanding: Challenges and Applications](https://md.research.elamur.ai/free/en/venues/eeuca/)**Kongqiang Wang, Peng Zhang, Quingli Tan*2026*
49. **[When Words Wear Masks: Detecting Malicious Intents and Hostile Impacts of Online Hate Speech](https://md.research.elamur.ai/free/en/papers/singhal-2026-when-words-wear-masks-detecting/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Priyansh Singhal, Piyush Joshi*2026*
50. [**A Hybrid DeBERTa and Gated Broad Learning System for Cyberbullying Detection in English Text arXiv:2506.16052**Devesh Kumar*2025*](https://md.research.elamur.ai/free/en/papers/kumar-2025-hybrid-deberta-gated-broad-learning/)
51. [**CourtPressGER: A German Court Decision to Press Release Summarization Dataset arXiv:2512.09434**Sebastian Nagl, Mohamed Elganayni, Melanie Pospisil, et al.*2025*](https://md.research.elamur.ai/free/en/papers/nagl-2025-courtpressger-german-court-decision-press/)
52. [**System Demo: Tool and Infrastructure for Offensive Language Error Analysis (OLEA) in English arXiv:2210.16398**Marie Grace, Xajavion "Jay" Seabrum, Dananjay Srinivas, et al.*2022*](https://md.research.elamur.ai/free/en/papers/grace-2022-system-demo-tool-infrastructure-offensive/)

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