🏙️ Works of Greater Boston from 2023

41 works · the most cited first · ← Greater Boston

1. Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language modelsPLOS Digital HealthTiffany H. Kung, Morgan Cheatham, Arielle Medenilla, et al.2023 · 4,168 citations
2. MIMIC-IV, a freely accessible electronic health record datasetScientific DataAlistair E. W. Johnson, Lucas Bulgarelli, Lu Shen, et al.2023 · 3,386 citations
3. ChatGPT Outperforms Crowd-Workers for Text-Annotation TasksProceedings of the National Academy of SciencesFabrizio Gilardi, Meysam Alizadeh, Maël Kubli2023 · 1,533 citations
4. Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language ModelsarXiv:2304.01852 · Meta-Radiology (2023)100,017Yiheng Liu, Tianle Han, Siyuan Ma, et al.2023 · 938 citations
5. Improving Factuality and Reasoning in Language Models through Multiagent DebatearXiv:2305.14325Yilun Du, Shuang Li, Antonio Torralba, et al.2023 · 565 citations
6. LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language ModelsarXiv:2308.11462Neel 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 Li2023 · 381 citations
7. AugGPT: Leveraging ChatGPT for Text Data AugmentationIEEE Transactions on Big DataHaixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li2023 · 306 citations
8. From Words to Watts: Benchmarking the Energy Costs of Large Language Model InferencearXiv:2310.03003Siddharth Samsi, Dan Zhao, Joseph McDonald, et al.2023 · 288 citations
9. Larger language models do in-context learning differentlyarXiv:2303.03846Jerry Wei, Jason Wei, Yi Tay, et al.2023 · 279 citations
10. LongLoRA: Efficient Fine-tuning of Long-Context Large Language ModelsarXiv:2309.12307Yukang Chen, Shengju Qian, Haotian Tang, et al.2023 · 265 citations
11. DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language ModelsarXiv:2309.03883Yung-Sung Chuang, Yujia Xie, Hongyin Luo, et al.2023 · 261 citations
12. LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic ProversConference on Empirical Methods in Natural Language Processing (EMNLP)Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.2023 · 171 citations
13. Low-Resource Languages Jailbreak GPT-4arXiv:2310.02446Zheng-Xin Yong, Cristina Menghini, Stephen H. Bach2023 · 168 citations
14. The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False DatasetsarXiv:2310.06824Samuel Marks, Max Tegmark2023 · 160 citations
15. Testing the Predictions of Surprisal Theory in 11 LanguagesTransactions of the Association for Computational Linguistics (TACL)Ethan G. Wilcox, Tiago Pimentel, Clara Meister, et al.2023 · 158 citations
16. The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual DatasetarXiv:2303.03915Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.2023 · 147 citations
17. Efficient Methods for Natural Language Processing: A SurveyTransactions of the Association for Computational Linguistics (TACL)Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.2023 · 145 citations
18. A fine-grained comparison of pragmatic language understanding in humans and language modelsJennifer Hu, Sammy Floyd, Olessia Jouravlev, et al.2023 · 136 citations
19. Prompting is not a substitute for probability measurements in large language modelsConference on Empirical Methods in Natural Language Processing (EMNLP)Jennifer Hu, Roger Levy2023 · 133 citations
20. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 128 citations
21. Machine Learning for Ancient Languages: A SurveyComputational LinguisticsThea Sommerschield, Yannis Assael, John Pavlopoulos, et al.2023 · 123 citations
22. Pretraining Language Models with Human PreferencesarXiv:2302.08582Tomasz Korbak, Kejian Shi, Angelica Chen, et al.2023 · 118 citations
23. Certifying LLM Safety against Adversarial PromptingarXiv:2309.02705Aounon Kumar, Chirag Agarwal, Suraj Srinivas, et al.2023 · 110 citations
24. Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-VerificationarXiv:2308.07921Aojun Zhou, Ke Wang, Zimu Lu, et al.2023 · 109 citations
25. We're Afraid Language Models Aren't Modeling AmbiguityConference on Empirical Methods in Natural Language Processing (EMNLP)Alisa Liu, Zhaofeng Wu, Julian Michael, et al.2023 · 108 citations
26. BLOOM+1: Adding Language Support to BLOOM for Zero-Shot PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, et al.2023 · 101 citations
27. Inverse Scaling: When Bigger Isn't BetterarXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQFIan R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.2023 · 99 citations
28. A Survey of Large Language Models in Medicine: Progress, Application, and ChallengearXiv:2311.05112Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.2023 · 87 citations
29. RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model OutputsAnnual Meeting of the Association for Computational Linguistics (ACL)Afra Feyza Akyurek, Ekin Akyurek, Ashwin Kalyan, et al.2023 · 87 citations
30. Multilingual Large Language Models Are Not (Yet) Code-SwitchersConference on Empirical Methods in Natural Language Processing (EMNLP)Ruochen Zhang, Samuel Cahyawijaya, Jan Christian Blaise Cruz, et al.2023 · 85 citations
31. ReLoRA: High-Rank Training Through Low-Rank UpdatesarXiv:2307.05695Vladislav Lialin, Namrata Shivagunde, Sherin Muckatira, et al.2023 · 74 citations
32. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 69 citations
33. Large Language Model Routing with Benchmark DatasetsarXiv:2309.15789Tal Shnitzer, Anthony Ou, Mirian Silva, et al.2023 · 61 citations
34. How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speechAnnual Meeting of the Association for Computational Linguistics (ACL)Aditya Yedetore, Tal Linzen, Robert Frank, et al.2023 · 48 citations
35. Findings of the Second WMT Shared Task on Sign Language Translation (WMT-SLT23)Conference on Machine Translation (WMT)Mathias Müller, Malihe Alikhani, Eleftherios Avramidis, et al.2023 · 39 citations
36. Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling ApproachesFindings of the Association for Computational LinguisticsDaniel Fried, Nicholas Tomlin, Jennifer Hu, et al.2023 · 36 citations
37. Expectations over Unspoken Alternatives Predict Pragmatic InferencesJennifer Hu, Roger Levy, Judith Degen, et al.2023 · 27 citations
38. What happens before and after: Multi-Event Commonsense in Event Coreference ResolutionConference of the European Chapter of the Association for Computational Linguistics (EACL)Sahithya Ravi, Chris Tanner, Raymond Ng, et al.2023 · 21 citations
39. DADA: Dialect Adaptation via Dynamic Aggregation of Linguistic RulesYanchen Liu, William Held, Diyi Yang2023 · 20 citations
40. Evaluating statistical language models as pragmatic reasonersarXiv:2305.01020Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.2023 · 18 citations
41. Data-driven Parsing Evaluation for Child-Parent InteractionsZoey Liu, Emily Prud'hommeaux2023 · 8 citations

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