---
title: "Who cites Tao Li — 191 papers of our library — Elamur Research"
description: "191 papers of the Elamur Research library cite the works of Tao Li, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/tao-li/cited-by/"
---
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# Who cites Tao Li

191 citations of their works from 191 papers of our library (of the 149,439 whose bibliographies we read) · 38 with a page here, the most cited first · [← Tao Li](https://md.research.elamur.ai/free/en/authors/tao-li/)

1. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
2. **[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*
3. **[Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks](https://md.research.elamur.ai/free/en/papers/zhang-2019-aspect-based-sentiment-classification-aspect/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chen Zhang, Qiuchi Li, Dawei Song*2019 · 808 citations*
4. **[Relational Graph Attention Network for Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/wang-2020-relational-graph-attention-network-aspect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Wang, Weizhou Shen, Yunyi Yang, et al.*2020 · 776 citations*
5. **[Aspect-Level Sentiment Analysis Via Convolution over Dependency Tree](https://md.research.elamur.ai/free/en/papers/sun-2019-aspect-level-sentiment-analysis-convolution/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kai Sun, Richong Zhang, Samuel Mensah, et al.*2019 · 499 citations*
6. [**GLaM: Efficient Scaling of Language Models with Mixture-of-Experts arXiv:2112.06905**Nan Du, Yanping Huang, Andrew M. Dai, et al.*2021 · 496 citations*](https://md.research.elamur.ai/free/en/papers/du-2021-glam-efficient-scaling-language-models/)
7. **[Exploiting BERT for End-to-End Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/li-2019-exploiting-bert-end-end-aspect/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Xin Li, Lidong Bing, Wenxuan Zhang, et al.*2019 · 417 citations*
8. **[Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification](https://md.research.elamur.ai/free/en/papers/tang-2020-dependency-graph-enhanced-dual-transformer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Tang, Donghong Ji, Chenliang Li, et al.*2020 · 397 citations*
9. **[A Unified Generative Framework for Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/yan-2021-unified-generative-framework-aspect-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hang Yan, Junqi Dai, Tuo Ji, et al.*2021 · 396 citations*
10. **[A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/jiang-2019-challenge-dataset-effective-models-aspect/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingnan Jiang, Lei Chen, Ruifeng Xu, et al.*2019 · 395 citations*
11. **[Position-Aware Tagging for Aspect Sentiment Triplet Extraction](https://md.research.elamur.ai/free/en/papers/xu-2020-position-aware-tagging-aspect-sentiment/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lu Xu, Hao Li, Wei Lu, et al.*2020 · 370 citations*
12. **[Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks](https://md.research.elamur.ai/free/en/papers/huang-2019-syntax-aware-aspect-level-sentiment/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Binxuan Huang, Kathleen Carley*2019 · 351 citations*
13. **[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*
14. **[Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classification](https://md.research.elamur.ai/free/en/papers/hu-2019-open-domain-targeted-sentiment-analysis/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minghao Hu, Yuxing Peng, Zhen Huang, et al.*2019 · 288 citations*
15. **[DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 259 citations*
16. **[NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark](https://md.research.elamur.ai/free/en/papers/sainz-2023-nlp-evaluation-trouble-need-measure/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oscar Sainz, Jon Campos, Iker García-Ferrero, et al.*2023 · 250 citations*
17. [**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/)
18. **[Stance Detection in COVID-19 Tweets](https://md.research.elamur.ai/free/en/papers/glandt-2021-stance-detection-covid-19-tweets/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kyle Glandt, Sarthak Khanal, Yingjie Li, et al.*2021 · 173 citations*
19. **[Arabic aspect based sentiment analysis using bidirectional GRU based models](https://md.research.elamur.ai/free/en/papers/m-abdelgwad-2021-arabic-aspect-based-sentiment-analysis/) [Journal of King Saud University - Computer and Information Sciences](https://md.research.elamur.ai/free/en/venues/journal-of-king-saud-university-computer-and-information-sciences/)**Mohammed M.Abdelgwad, Taysir Hassan A Soliman, Ahmed I.Taloba, et al.*2021 · 127 citations*
20. [**Large Language Model Alignment: A Survey arXiv:2309.15025**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
21. **[KoBBQ: Korean Bias Benchmark for Question Answering](https://md.research.elamur.ai/free/en/papers/jin-2024-kobbq-korean-bias-benchmark-question/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiho Jin, Jiseon Kim, Nayeon Lee, et al.*2024 · 78 citations*
22. **[Infusing Knowledge from Wikipedia to Enhance Stance Detection](https://md.research.elamur.ai/free/en/papers/he-2022-infusing-knowledge-wikipedia-enhance-stance/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Zihao He, Negar Mokhberian, Kristina Lerman*2022 · 72 citations*
23. **[FORK: A Bite-Sized Test Set for Probing Culinary Cultural Biases in Commonsense Reasoning Models](https://md.research.elamur.ai/free/en/papers/palta-2023-fork-bite-sized-test-set/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shramay Palta, Rachel Rudinger*2023 · 67 citations*
24. **[The Art of Saying No: Contextual Noncompliance in Language Models](https://md.research.elamur.ai/free/en/papers/brahman-2024-art-saying-no-contextual-noncompliance/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.*2024 · 56 citations*
25. **[Target-Aware Data Augmentation for Stance Detection](https://md.research.elamur.ai/free/en/papers/li-2021-target-aware-data-augmentation-stance/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yingjie Li, Cornelia Caragea*2021 · 56 citations*
26. **[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*
27. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
28. **[A Multi-Task Learning Framework for Multi-Target Stance Detection](https://md.research.elamur.ai/free/en/papers/li-2021-multi-task-learning-framework-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingjie Li, Cornelia Caragea*2021 · 31 citations*
29. [**Pushing the Limits of ChatGPT on NLP Tasks arXiv:2306.09719**Xiaofei Sun, Linfeng Dong, Xiaoya Li, et al.*2023 · 28 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-pushing-limits-chatgpt-nlp-tasks/)
30. **[From Selection to Generation: A Survey of LLM-based Active Learning](https://md.research.elamur.ai/free/en/papers/xia-2025-selection-generation-survey-llm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie, et al.*2025 · 22 citations*
31. **[BasqBBQ: A QA Benchmark for Assessing Social Biases in LLMs for Basque, a Low-Resource Language](https://md.research.elamur.ai/free/en/papers/zulaika-2025-basqbbq-qa-benchmark-assessing-social/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Muitze Zulaika, Xabier Saralegi*2025 · 15 citations*
32. **[A Challenge Dataset and Effective Models for Conversational Stance Detection](https://md.research.elamur.ai/free/en/papers/niu-2024-challenge-dataset-effective-models-conversational/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Fuqiang Niu, Min Yang, Ang Li, et al.*2024 · 12 citations*
33. **[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*
34. **[Are Social Biases in LLMs Consistent across Generative Tasks? A Case Study for Basque](https://md.research.elamur.ai/free/en/papers/zulaika-2026-are-social-biases-llms-consistent/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Muitze Zulaika, Xabier Saralegi, Julia Shershneva, et al.*2026*
35. **[Beyond Bias Scores: Unmasking Vacuous Neutrality in Small Language Models](https://md.research.elamur.ai/free/en/papers/manduru-2026-beyond-bias-scores-unmasking-vacuous/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sumanth Manduru, Carlotta Domeniconi*2026*
36. **[BiasGRPO: Stabilizing Bias Mitigation in High-Variance Reward Landscapes via Group-Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/reddy-2026-biasgrpo-stabilizing-bias-mitigation-high/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Saket Reddy, Ke Yang, ChengXiang Zhai*2026*
37. **[Investigating Gender Stereotypes in Large Language Models via Social Determinants of Health](https://md.research.elamur.ai/free/en/papers/ngo-2026-investigating-gender-stereotypes-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Trung Hieu Ngo, Adrien Bazoge, Solen Quiniou, et al.*2026*
38. **[Interactive Learning Approach for Arabic Target-Based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/balla-2021-interactive-learning-approach-arabic-target/) [Recent Advances in Natural Language Processing (RANLP)](https://md.research.elamur.ai/free/en/venues/ranlp/)**Husamelddin Balla, Marisa Llorens Salvador, Sarah Jane Delany*2021*

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

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