---
title: "Who cites Haochen Liu — 82 papers of our library"
description: "82 papers of the Elamur Research library cite the works of Haochen Liu, found in their bibliographies; the most cited first."
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---
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# Who cites Haochen Liu

95 citations of their works from 82 papers of our library (of the 149,439 whose bibliographies we read) · 27 with a page here, the most cited first · [← Haochen Liu](https://md.research.elamur.ai/free/en/authors/haochen-liu/)

1. [**Training language models to follow instructions with human feedback arXiv:2203.02155**Long Ouyang, Jeff Wu, Xu Jiang, et al.*2022 · 10,224 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2022-training-language-models-follow-instructions/)
2. [**OPT: Open Pre-trained Transformer Language Models arXiv:2205.01068**Susan Zhang, Stephen Roller, Naman Goyal, et al.*2022 · 1,755 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2022-opt-open-pre-trained-transformer/)
3. **[Language (Technology) is Power: A Critical Survey of “Bias” in NLP](https://md.research.elamur.ai/free/en/papers/blodgett-2020-language-technology-is-power-critical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.*2020 · 1,716 citations*
4. [**LaMDA: Language Models for Dialog Applications arXiv:2201.08239**Romal Thoppilan, Daniel De Freitas, Jamie Hall, et al.*2022 · 1,344 citations*](https://md.research.elamur.ai/free/en/papers/thoppilan-2022-lamda-language-models-dialog-applications/)
5. **[Bias and Fairness in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/gallegos-2023-bias-fairness-large-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.*2023 · 1,082 citations*
6. **[A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/fan-2024-survey-rag-meeting-llms-towards/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li*2024 · 1,010 citations*
7. **[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*
8. [**Towards Understanding and Mitigating Social Biases in Language Models arXiv:2106.13219**Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, et al.*2021 · 271 citations*](https://md.research.elamur.ai/free/en/papers/liang-2021-towards-understanding-mitigating-social-biases/)
9. **[Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation](https://md.research.elamur.ai/free/en/papers/dinan-2020-queens-are-powerful-too-mitigating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Emily Dinan, Angela Fan, Adina Williams, et al.*2020 · 270 citations*
10. **[Societal Biases in Language Generation: Progress and Challenges](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.*2021 · 257 citations*
11. [**Recipes for Safety in Open-domain Chatbots arXiv:2010.07079**Jing Xu, Da Ju, Margaret Li, et al.*2020 · 201 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-recipes-safety-open-domain-chatbots/)
12. [**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/)
13. **[“I'm sorry to hear that”: Finding New Biases in Language Models with a Holistic Descriptor Dataset](https://md.research.elamur.ai/free/en/papers/smith-2022-i-m-sorry-hear-that/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eric Michael Smith, Melissa Hall, Melanie Kambadur, et al.*2022 · 167 citations*
14. **[Does Gender Matter? Towards Fairness in Dialogue Systems](https://md.research.elamur.ai/free/en/papers/liu-2020-does-gender-matter-fairness-dialogue/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Haochen Liu, Jamell Dacon, Wenqi Fan, et al.*2020 · 133 citations*
15. **[Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey](https://md.research.elamur.ai/free/en/papers/kumar-2023-language-generation-models-can-cause/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.*2023 · 90 citations*
16. [**AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model arXiv:2208.01448**Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald, et al.*2022 · 84 citations*](https://md.research.elamur.ai/free/en/papers/soltan-2022-alexatm-20b-few-shot-learning/)
17. **[Sociodemographic Bias in Language Models: A Survey and Forward Path](https://md.research.elamur.ai/free/en/papers/gupta-2023-sociodemographic-bias-language-models-survey/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Vipul Gupta, Pranav Narayanan Venkit, Shomir Wilson, et al.*2023 · 40 citations*
18. **[User-Centric Gender Rewriting](https://md.research.elamur.ai/free/en/papers/alhafni-2022-user-centric-gender-rewriting/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bashar Alhafni, Nizar Habash, Houda Bouamor*2022 · 29 citations*
19. **[The Arabic Parallel Gender Corpus 2.0: Extensions and Analyses](https://md.research.elamur.ai/free/en/papers/alhafni-2022-arabic-parallel-gender-corpus-2/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Bashar Alhafni, Nizar Habash, Houda Bouamor*2022 · 21 citations*
20. **[Towards a Deep Multi-layered Dialectal Language Analysis: A Case Study of African-American English](https://md.research.elamur.ai/free/en/papers/dacon-2022-deep-multi-layered-dialectal-language/) [Workshop on Bridging Human–Computer Interaction and Natural Language Processing](https://md.research.elamur.ai/free/en/venues/hcinlp/)**Jamell Dacon*2022 · 13 citations*
21. **[Speciesist Language and Nonhuman Animal Bias in English Masked Language Models](https://md.research.elamur.ai/free/en/papers/takeshita-2022-speciesist-language-nonhuman-animal-bias/) [Information Processing & Management](https://md.research.elamur.ai/free/en/venues/information-processing-management/)**Masashi Takeshita, Rafal Rzepka, Kenji Araki*2022 · 11 citations*
22. **[Evaluating and Mitigating Inherent Linguistic Bias of African American English through Inference](https://md.research.elamur.ai/free/en/papers/dacon-2022-evaluating-mitigating-inherent-linguistic-bias/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jamell Dacon, Haochen Liu, Jiliang Tang*2022 · 6 citations*
23. **[The User-Aware Arabic Gender Rewriter](https://md.research.elamur.ai/free/en/papers/alhafni-2023-user-aware-arabic-gender-rewriter/) [Workshop on Gender-Inclusive Translation Technologies](https://md.research.elamur.ai/free/en/venues/gitt/)**Bashar Alhafni, Ossama Obeid, Nizar Habash*2023 · 5 citations*
24. **[Leveraging Syntactic Dependencies in Disambiguation: The Case of African American English](https://md.research.elamur.ai/free/en/papers/previlon-2024-leveraging-syntactic-dependencies-disambiguation-case/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Wilermine Previlon, Alice Rozet, Jotsna Gowda, et al.*2024 · 4 citations*
25. **[CAI@LTEDI 2026: Multilingual Gender Inclusive Language Generation using Instruction-Guided mT5 Transformer Model](https://md.research.elamur.ai/free/en/papers/nair-2026-cai-ltedi-2026-multilingual-gender/) [Workshop on Language Technology for Equality, Diversity, Inclusion](https://md.research.elamur.ai/free/en/venues/ltedi/)**Aiswariya p Nair, Sree S Bhagya, Chinnu Jacob*2026*
26. [**Evaluating the Usage of African-American Vernacular English in Large Language Models arXiv:2602.21485**Deja Dunlap, R. Thomas McCoy*2026*](https://md.research.elamur.ai/free/en/papers/dunlap-2026-evaluating-usage-african-american-vernacular/)
27. [**LLMs Silently Correct African American English: Auditing and Mitigating Dialect Bias via Activation Steering arXiv:2607.06845**Huan Wu, Ali Emami, Muhammad Furquan Hassan, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wu-2026-llms-silently-correct-african-american/)

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

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