Elamur Research⌕
☰
home / authors / Trieu H. Trinh / cited by

Who cites Trieu H. Trinh

548 citations of their works from 521 papers of our library (of the 149,439 whose bibliographies we read) · 177 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Trieu H. Trinh

1 2

  1. Language Models are Few-Shot LearnersarXiv:2005.14165Tom B. Brown, Benjamin Mann, Nick Ryder, et al.2020 · 14,178 citations
  2. Exploring the Limits of Transfer Learning with a Unified Text-to-Text TransformerarXiv:1910.10683Colin Raffel, Noam Shazeer, Adam Roberts, et al.2019 · 11,325 citations
  3. RoBERTa: A Robustly Optimized BERT Pretraining ApproacharXiv:1907.11692Yinhan Liu, Myle Ott, Naman Goyal, et al.2019 · 9,837 citations
  4. Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language ProcessingACM Computing SurveysPengfei Liu, Weizhe Yuan, Jinlan Fu, et al.2021 · 5,423 citations
  5. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,728 citations
  6. Longformer: The Long-Document TransformerarXiv:2004.05150Iz Beltagy, Matthew E. Peters, Arman Cohan2020 · 3,880 citations
  7. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  8. UNITER: UNiversal Image-TExt Representation LearningLecture notes in computer scienceYen-Chun Chen, Linjie Li, Licheng Yu, et al.2019 · 2,418 citations
  9. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,269 citations
  10. DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsarXiv:2402.03300Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.2024 · 2,115 citations
  11. Making Pre-trained Language Models Better Few-shot LearnersAnnual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Adam Fisch, Danqi Chen2021 · 1,987 citations
  12. AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated PromptsConference on Empirical Methods in Natural Language Processing (EMNLP)Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.2020 · 1,909 citations
  13. Unsupervised Data Augmentation for Consistency TrainingarXiv:1904.12848Qizhe Xie, Zihang Dai, Eduard Hovy, et al.2019 · 1,871 citations
  14. DeBERTa: Decoding-enhanced BERT with Disentangled AttentionarXiv:2006.03654Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.2020 · 1,828 citations
  15. Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language InferenceConference of the European Chapter of the Association for Computational Linguistics (EACL)Timo Schick, Hinrich Schütze2021 · 1,817 citations
  16. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
  17. CommonsenseQA: A Question Answering Challenge Targeting Commonsense KnowledgeConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Alon Talmor, Jonathan Herzig, Nicholas Lourie, et al.2019 · 1,676 citations
  18. Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A SurveyACM Computing SurveysBonan Min, Hayley Ross, Elior Sulem, et al.2021 · 1,556 citations
  19. How Can We Know What Language Models Know?Transactions of the Association for Computational Linguistics (TACL)Zhengbao Jiang, Frank F. Xu, Jun Araki, et al.2020 · 1,521 citations
  20. GLM: General Language Model Pretraining with Autoregressive Blank InfillingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhengxiao Du, Yujie Qian, Xiao Liu, et al.2022 · 1,455 citations
  21. CTRL: A Conditional Transformer Language Model for Controllable GenerationarXiv:1909.05858Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al.2019 · 1,291 citations
  22. It's Not Just Size That Matters: Small Language Models Are Also Few-Shot LearnersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Timo Schick, Hinrich Schütze2021 · 1,132 citations
  23. Big Bird: Transformers for Longer SequencesConference on Neural Information Processing Systems (NeurIPS)Manzil Zaheer, Guru Guruganesh, Avinava Dubey, et al.2020 · 1,023 citations
  24. Solving Quantitative Reasoning Problems with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Aitor Lewkowycz, Anders Andreassen, David Dohan, et al.2022 · 992 citations
  25. MPNet: Masked and Permuted Pre-training for Language UnderstandingarXiv:2004.09297Kaitao Song, Xu Tan, Tao Qin, et al.2020 · 957 citations
  26. Calibrate Before Use: Improving Few-Shot Performance of Language ModelsarXiv:2102.09690Tony Z. Zhao, Eric Wallace, Shi Feng, et al.2021 · 825 citations
  27. Explain Yourself! Leveraging Language Models for Commonsense ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, et al.2019 · 701 citations
  28. DAPO: An Open-Source LLM Reinforcement Learning System at ScalearXiv:2503.14476Qiying Yu, Zheng Zhang, Ruofei Zhu, et al.2025 · 668 citations
  29. Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language ModelarXiv:2201.11990Shaden Smith, Mostofa Patwary, Brandon Norick, et al.2022 · 615 citations
  30. Few-shot Learning with Multilingual Language ModelsarXiv:2112.10668Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, et al.2021 · 500 citations
  31. PPT: Pre-trained Prompt Tuning for Few-shot LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxian Gu, Xu Han, Zhiyuan Liu, et al.2022 · 471 citations
  32. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsarXiv:2310.02255Pan Lu, Hritik Bansal, Tony Xia, et al.2023 · 468 citations
  33. OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific ProblemsAnnual Meeting of the Association for Computational Linguistics (ACL)Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.2024 · 456 citations
  34. The Falcon Series of Open Language ModelsarXiv:2311.16867Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.2023 · 443 citations
  35. The FineWeb Datasets: Decanting the Web for the Finest Text Data at ScaleConference on Neural Information Processing Systems (NeurIPS)Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al.2024 · 434 citations
  36. Commonsense Knowledge Mining from Pretrained ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Joe Davison, Joshua Feldman, Alexander Rush2019 · 413 citations
  37. UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-TrainingarXiv:2002.12804Hangbo Bao, Li Dong, Furu Wei, et al.2020 · 395 citations
  38. ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading ComprehensionarXiv:1810.12885Sheng Zhang, Xiaodong Liu, Jingjing Liu, et al.2018 · 388 citations
  39. Mind the GAP: A Balanced Corpus of Gendered Ambiguous PronounsKellie Webster, Marta Recasens, Vera Axelrod, et al.2018 · 358 citations
  40. DeepSeek-V3.2: Pushing the Frontier of Open Large Language ModelsarXiv:2512.02556DeepSeek-AI, Aixin Liu, Aoxue Mei, et al.2025 · 341 citations
  41. ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and GenerationarXiv:2107.02137Yu Sun, Shuohuan Wang, Shikun Feng, et al.2021 · 332 citations
  42. How many data points is a prompt worth?Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Teven Le Scao, Alexander Rush2021 · 320 citations
  43. Large Language Models for Mathematical Reasoning: Progresses and ChallengesConference of the European Chapter of the Association for Computational Linguistics (EACL)Janice Ahn, Rishu Verma, Renze Lou, et al.2024 · 280 citations
  44. Large Language Monkeys: Scaling Inference Compute with Repeated SamplingarXiv:2407.21787Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.2024 · 270 citations
  45. Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 253 citations
  46. Evaluating Commonsense in Pre-trained Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceXuhui Zhou, Yue Zhang, Leyang Cui, et al.2019 · 235 citations
  47. Coreferential Reasoning Learning for Language RepresentationConference on Empirical Methods in Natural Language Processing (EMNLP)Deming Ye, Yankai Lin, Jiaju Du, et al.2020 · 228 citations
  48. A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource LanguagesAnnual Meeting of the Association for Computational Linguistics (ACL)Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot2020 · 222 citations
  49. Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-Trained Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Bill Yuchen Lin, Seyeon Lee, Rahul Khanna, et al.2020 · 218 citations
  50. Training Question Answering Models From Synthetic DataConference on Empirical Methods in Natural Language Processing (EMNLP)Raul Puri, Ryan Spring, Mohammad Shoeybi, et al.2020 · 208 citations
  51. Measuring Multimodal Mathematical Reasoning with MATH-Vision DatasetConference on Neural Information Processing Systems (NeurIPS)Ke Wang, Junting Pan, Weikang Shi, et al.2024 · 203 citations
  52. AlphaEvolve: A coding agent for scientific and algorithmic discoveryarXiv:2506.13131Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al.2025 · 202 citations
  53. Will we run out of data? Limits of LLM scaling based on human-generated dataarXiv:2211.04325Pablo Villalobos, Anson Ho, Jaime Sevilla, et al.2022 · 198 citations
  54. COCO-LM: Correcting and Contrasting Text Sequences for Language Model PretrainingarXiv:2102.08473Yu Meng, Chenyan Xiong, Payal Bajaj, et al.2021 · 198 citations
  55. Generative Data Augmentation for Commonsense ReasoningFindings of the Association for Computational LinguisticsYiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.2020 · 198 citations
  56. Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP ResearchersarXiv:2409.04109Chenglei Si, Diyi Yang, Tatsunori Hashimoto2024 · 196 citations
  57. CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 LanguagesLanguage Resources and Evaluation Conference (LREC)Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, et al.2023 · 181 citations
  58. 8-bit Optimizers via Block-wise QuantizationarXiv:2110.02861Tim Dettmers, Mike Lewis, Sam Shleifer, et al.2021 · 181 citations
  59. Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal ProofsarXiv:2210.12283Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.2022 · 178 citations
  60. Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language ModelsarXiv:2410.07985Bofei Gao, Feifan Song, Zhe Yang, et al.2024 · 163 citations
  61. Language models show human-like content effects on reasoning tasksarXiv:2207.07051Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, et al.2022 · 162 citations
  62. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
  63. MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Peng Xu, Mostofa Patwary, Mohammad Shoeybi, et al.2020 · 158 citations
  64. Towards a Cleaner Document-Oriented Multilingual Crawled CorpusLanguage Resources and Evaluation Conference (LREC)Julien Abadji, Pedro Ortiz Suarez, Laurent Romary, et al.2022 · 156 citations
  65. DeepSeek-V4: Towards Highly Efficient Million-Token Context IntelligencearXiv:2606.19348DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.2026 · 122 citations
  66. A Surprisingly Robust Trick for the Winograd Schema ChallengeAnnual Meeting of the Association for Computational Linguistics (ACL)Vid Kocijan, Ana-Maria Cretu, Oana-Maria Camburu, et al.2019 · 121 citations
  67. Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations
  68. Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language ModelsarXiv:2208.03306Margaret Li, Suchin Gururangan, Tim Dettmers, et al.2022 · 114 citations
  69. Efficient Large Scale Language Modeling with Mixtures of ExpertsarXiv:2112.10684Mikel Artetxe, Shruti Bhosale, Naman Goyal, et al.2021 · 113 citations
  70. minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language ModelsarXiv:2203.13112Kanishka Misra2022 · 102 citations
  71. FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AIarXiv:2411.04872Elliot Glazer, Ege Erdil, Tamay Besiroglu, et al.2024 · 97 citations
  72. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
  73. Probing Across Time: What Does RoBERTa Know and When?Findings of the Association for Computational LinguisticsLeo Z. Liu, Yizhong Wang, Jungo Kasai, et al.2021 · 96 citations
  74. GLM-5: from Vibe Coding to Agentic EngineeringarXiv:2602.15763Aohan Zeng, Xin Lv, Zhenyu Hou, et al.2026 · 95 citations
  75. PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical CompetitionConference on Neural Information Processing Systems (NeurIPS)George Tsoukalas, Jasper Lee, John Jennings, et al.2024 · 93 citations
  76. Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language ModelsarXiv:2503.06749Wenxuan Huang, Bohan Jia, Zijie Zhai, et al.2025 · 92 citations
  77. LLMs Can't Plan, But Can Help Planning in LLM-Modulo FrameworksarXiv:2402.01817 · Proceedings of the 41 st International Conference on Machine Learning, Vienna, Austria. PMLR 235, 2024Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, et al.2024 · 88 citations
  78. The KnowRef Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora ResolutionAli Emami, Paul Trichelair, Adam Trischler, et al.2019 · 73 citations
  79. NormBank: A Knowledge Bank of Situational Social NormsAnnual Meeting of the Association for Computational Linguistics (ACL)Caleb Ziems, Jane Dwivedi-Yu, Yi-Chia Wang, et al.2023 · 69 citations
  80. It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense ReasoningFindings of the Association for Computational LinguisticsAlexey Tikhonov, Max Ryabinin2021 · 69 citations
  81. Hypothesis Generation with Large Language ModelsarXiv:2404.04326Yangqiaoyu Zhou; Haokun Liu; Tejes Srivastava; Hongyuan Mei;, Chenhao Tan2024 · 68 citations
  82. Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-CorrectionarXiv:2508.03613Yong Lin, Shange Tang, Bohan Lyu, et al.2025 · 67 citations
  83. Kimi K2.5: Visual Agentic IntelligencearXiv:2602.02276Kimi Team, Tongtong Bai, Yifan Bai, et al.2026 · 66 citations
  84. Automatic Story Generation: Challenges and AttemptsWorkshop on Narrative UnderstandingAmal Alabdulkarim, Siyan Li, Xiangyu Peng2021 · 61 citations
  85. Autonomous LLM-driven research from data to human-verifiable research papersNEJM AITal Ifargan, Lukas Hafner, Maor Kern, et al.2024 · 57 citations
  86. OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AIConference on Neural Information Processing Systems (NeurIPS)Zhen Huang, Zengzhi Wang, Shijie Xia, et al.2024 · 56 citations
  87. Easy-to-Hard Generalization: Scalable Alignment Beyond Human SupervisionConference on Neural Information Processing Systems (NeurIPS)Zhiqing Sun, Longhui Yu, Yikang Shen, et al.2024 · 51 citations
  88. Formal Mathematical Reasoning: A New Frontier in AIarXiv:2412.16075Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.2024 · 49 citations
  89. PanGu-Coder: Program Synthesis with Function-Level Language ModelingarXiv:2207.11280Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, et al.2022 · 49 citations
  90. Modern Baselines for SPARQL Semantic ParsingInternational ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)Debayan Banerjee, Pranav Ajit Nair, Jivat Neet Kaur, et al.2022 · 48 citations
  91. An In-Context Learning Agent for Formal Theorem-ProvingarXiv:2310.04353Amitayush Thakur, George Tsoukalas, Yeming Wen, et al.2023 · 47 citations
  92. Seed-Prover: Deep and Broad Reasoning for Automated Theorem ProvingarXiv:2507.23726Luoxin Chen, Jinming Gu, Liankai Huang, et al.2025 · 46 citations
  93. A Survey on Deep Learning for Theorem ProvingarXiv:2404.09939Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.2024 · 46 citations
  94. MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math DataScientific DataMeng Fang, Xiangpeng Wan, Fei Lu, et al.2024 · 46 citations
  95. Key-Point-Driven Data Synthesis with its Enhancement on Mathematical ReasoningProceedings of the AAAI Conference on Artificial IntelligenceYiming Huang, Xiao Liu, Yeyun Gong, et al.2024 · 45 citations
  96. Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem SolvingarXiv:2405.12205Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, et al.2024 · 45 citations
  97. WikiCREM: A Large Unsupervised Corpus for Coreference ResolutionConference on Empirical Methods in Natural Language Processing (EMNLP)Vid Kocijan, Oana-Maria Camburu, Ana-Maria Cretu, et al.2019 · 41 citations
  98. Towards Robust Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Thang Luong, Dawsen Hwang, Hoang H Nguyen, et al.2025 · 40 citations
  99. A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic SystemsarXiv:2504.09037Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.2025 · 39 citations
  100. Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn'tarXiv:2503.16219Quy-Anh Dang, Chris Ngo2025 · 37 citations

1 2

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/trieu-h-trinh/cited-by/