---
title: "Stanford University — works"
description: "248 works by researchers of Stanford University in our library · page 1 of 3, the most cited first."
canonical: "https://research.elamur.ai/free/en/universities/stanford-university/works/"
---
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# Works of Stanford University

248 works · page 1 of 3 · the most cited first · [← Stanford University](https://md.research.elamur.ai/free/en/universities/stanford-university/)

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1. [**Latent Dirichlet Allocation**David M. Blei, Andrew Y. Ng, Michael I. Jordan*2003 · 28,297 citations*](https://md.research.elamur.ai/free/en/papers/blei-2003-latent-dirichlet-allocation/)
2. [**The Anatomy of a Large-Scale Hypertextual Web Search Engine**Sergey Brin, Lawrence Page*1998 · 16,227 citations*](https://md.research.elamur.ai/free/en/papers/brin-1998-anatomy-large-scale-hypertextual-web/)
3. [**SQuAD: 100,000+ Questions for Machine Comprehension of Text**Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, et al.*2016 · 9,488 citations*](https://md.research.elamur.ai/free/en/papers/rajpurkar-2016-squad-100-000-questions-machine/)
4. [**The Stanford CoreNLP Natural Language Processing Toolkit**Christopher Manning, Mihai Surdeanu, John Bauer, et al.*2014 · 8,620 citations*](https://md.research.elamur.ai/free/en/papers/manning-2014-stanford-corenlp-natural-language-processing/)
5. [**Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations**Ranjay Krishna, Yuke Zhu, Oliver Groth, et al.*2016 · 5,747 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2016-visual-genome-connecting-language-vision/)
6. [**Inductive Representation Learning on Large Graphs**William L. Hamilton, Rex Ying, Jure Leskovec*2017 · 4,687 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2017-inductive-representation-learning-large-graphs/)
7. [**Learning Word Vectors for Sentiment Analysis**Andrew L. Maas, Raymond E. Daly, Peter T. Pham, et al.*2011 · 4,272 citations*](https://md.research.elamur.ai/free/en/papers/maas-2011-learning-word-vectors-sentiment-analysis/)
8. [**Accurate Unlexicalized Parsing**Dan Klein, Christopher D. Manning*2003 · 3,942 citations*](https://md.research.elamur.ai/free/en/papers/klein-2003-accurate-unlexicalized-parsing/)
9. [**Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling**Jenny Rose Finkel, Trond Grenager, Christopher Manning*2005 · 3,618 citations*](https://md.research.elamur.ai/free/en/papers/finkel-2005-incorporating-non-local-information-into/)
10. [**Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network**Kristina Toutanova, Dan Klein, Christopher D. Manning, et al.*2003 · 3,559 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2003-feature-rich-part-speech-tagging/)
11. [**HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering**Zhilin Yang, Peng Qi, Saizheng Zhang, et al.*2018 · 3,489 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-hotpotqa-dataset-diverse-explainable-multi/)
12. [**Know What You Don't Know: Unanswerable Questions for SQuAD**Pranav Rajpurkar, Robin Jia, Percy Liang*2018 · 3,360 citations*](https://md.research.elamur.ai/free/en/papers/rajpurkar-2018-know-what-you-don-t/)
13. [**A Diversity-Promoting Objective Function for Neural Conversation Models**Jiwei Li, Michel Galley, Chris Brockett, et al.*2016 · 2,925 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-diversity-promoting-objective-function-neural/)
14. [**Generating Typed Dependency Parses from Phrase Structure Parses**Marie-Catherine de Marneffe, Bill MacCartney, Christopher D. Manning*2006 · 2,886 citations*](https://md.research.elamur.ai/free/en/papers/marneffe-2006-generating-typed-dependency-parses-phrase/)
15. [**Lost in the Middle: How Language Models Use Long Contexts**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,540 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/)
16. [**Learning Important Features Through Propagating Activation Differences**Avanti Shrikumar, Peyton Greenside, Anshul Kundaje*2017 · 2,377 citations*](https://md.research.elamur.ai/free/en/papers/shrikumar-2017-learning-important-features-through-propagating/)
17. [**Generating Sentences from a Continuous Space**Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al.*2016 · 2,367 citations*](https://md.research.elamur.ai/free/en/papers/bowman-2016-generating-sentences-continuous-space/)
18. [**Stanza: A Python Natural Language Processing Toolkit for Many Human Languages**Peng Qi, Yuhao Zhang, Yuhui Zhang, et al.*2020 · 2,347 citations*](https://md.research.elamur.ai/free/en/papers/qi-2020-stanza-python-natural-language-processing/)
19. [**A Fast and Accurate Dependency Parser using Neural Networks**Danqi Chen, Christopher Manning*2014 · 2,301 citations*](https://md.research.elamur.ai/free/en/papers/chen-2014-fast-accurate-dependency-parser-neural/)
20. [**Reading Wikipedia to Answer Open-Domain Questions**Danqi Chen, Adam Fisch, Jason Weston, et al.*2017 · 2,250 citations*](https://md.research.elamur.ai/free/en/papers/chen-2017-reading-wikipedia-answer-open-domain/)
21. [**Emergent Abilities of Large Language Models**Jason Wei, Yi Tay, Rishi Bommasani, et al.*2022 · 2,215 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/)
22. [**GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering**Drew A. Hudson, Christopher D. Manning*2019 · 1,997 citations*](https://md.research.elamur.ai/free/en/papers/hudson-2019-gqa-new-dataset-real-world/)
23. [**Adversarial Examples for Evaluating Reading Comprehension Systems**Robin Jia, Percy Liang*2017 · 1,935 citations*](https://md.research.elamur.ai/free/en/papers/jia-2017-adversarial-examples-evaluating-reading-comprehension/)
24. [**ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT**Omar Khattab, Matei Zaharia*2020 · 1,776 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2020-colbert-efficient-effective-passage/)
25. [**Universal Dependencies v1: A Multilingual Treebank Collection**Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, et al.*2016 · 1,739 citations*](https://md.research.elamur.ai/free/en/papers/nivre-2016-universal-dependencies-v1-multilingual-treebank/)
26. [**Deep Unsupervised Learning using Nonequilibrium Thermodynamics**Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, et al.*2015 · 1,588 citations*](https://md.research.elamur.ai/free/en/papers/sohl-dickstein-2015-deep-unsupervised-learning-using-nonequilibrium/)
27. [**Multitask Prompted Training Enables Zero-Shot Task Generalization**Victor Sanh, Albert Webson, Colin Raffel, et al.*2021 · 1,577 citations*](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/)
28. [**Semantic Compositionality through Recursive Matrix-Vector Spaces**Richard Socher, Brody Huval, Christopher D. Manning, et al.*2012 · 1,559 citations*](https://md.research.elamur.ai/free/en/papers/socher-2012-semantic-compositionality-through-recursive-matrix/)
29. [**CoQA: A Conversational Question Answering Challenge**Siva Reddy, Danqi Chen, Christopher D. Manning*2019 · 1,541 citations*](https://md.research.elamur.ai/free/en/papers/reddy-2019-coqa-conversational-question-answering-challenge/)
30. [**Score-Based Generative Modeling through Stochastic Differential Equations**Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, et al.*2020 · 1,528 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-score-based-generative-modeling-through/)
31. [**Multiword Expressions: A Pain in the Neck for NLP**Ivan A. Sag, Timothy Baldwin, Francis Bond, et al.*2002 · 1,497 citations*](https://md.research.elamur.ai/free/en/papers/sag-2002-multiword-expressions-pain-neck-nlp/)
32. [**Deep Reinforcement Learning for Dialogue Generation**Jiwei Li, Will Monroe, Alan Ritter, et al.*2016 · 1,479 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-deep-reinforcement-learning-dialogue-generation/)
33. [**Understanding Black-box Predictions via Influence Functions**Pang Wei Koh, Percy Liang*2017 · 1,478 citations*](https://md.research.elamur.ai/free/en/papers/koh-2017-understanding-black-box-predictions-influence/)
34. [**Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions**Richard Socher, Jeffrey Pennington, Eric H. Huang, et al.*2011 · 1,411 citations*](https://md.research.elamur.ai/free/en/papers/socher-2011-semi-supervised-recursive-autoencoders-predicting/)
35. [**Improving Word Representations via Global Context and Multiple Word Prototypes**Eric Huang, Richard Socher, Christopher Manning, et al.*2012 · 1,349 citations*](https://md.research.elamur.ai/free/en/papers/huang-2012-improving-word-representations-global-context/)
36. [**Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change**William L. Hamilton, Jure Leskovec, Dan Jurafsky*2016 · 1,270 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2016-diachronic-word-embeddings-reveal-statistical/)
37. [**Generative Modeling by Estimating Gradients of the Data Distribution**Yang Song, Stefano Ermon*2019 · 1,155 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-generative-modeling-estimating-gradients-data/)
38. [**The Stanford Typed Dependencies Representation**Marie-Catherine de Marneffe, Christopher D. Manning*2008 · 1,144 citations*](https://md.research.elamur.ai/free/en/papers/marneffe-2008-stanford-typed-dependencies-representation/)
39. [**Baselines and Bigrams: Simple, Good Sentiment and Topic Classification**Sida Wang, Christopher Manning*2012 · 1,116 citations*](https://md.research.elamur.ai/free/en/papers/wang-2012-baselines-bigrams-simple-good-sentiment/)
40. [**SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity**Eneko Agirre, Daniel Cer, Mona Diab, et al.*2012 · 1,107 citations*](https://md.research.elamur.ai/free/en/papers/agirre-2012-semeval-2012-task-6-pilot/)
41. [**Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them**Mirac Suzgun, Nathan Scales, Nathanael Schärli, et al.*2023 · 1,094 citations*](https://md.research.elamur.ai/free/en/papers/suzgun-2023-challenging-big-bench-tasks-whether/)
42. [**Enriching the Knowledge Sources Used in a Maximum Entropy Part-of-Speech Tagger**Kristina Toutanova, Christopher D. Manning*2000 · 1,082 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2000-enriching-knowledge-sources-used-maximum/)
43. [**Bias and Fairness in Large Language Models: A Survey**Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.*2023 · 1,072 citations*](https://md.research.elamur.ai/free/en/papers/gallegos-2023-bias-fairness-large-language-models/)
44. [**QuAC: Question Answering in Context**Eunsol Choi, He He, Mohit Iyyer, et al.*2018 · 1,057 citations*](https://md.research.elamur.ai/free/en/papers/choi-2018-quac-question-answering-context/)
45. [**Graph Convolution over Pruned Dependency Trees Improves Relation Extraction**Yuhao Zhang, Peng Qi, Christopher D. Manning*2018 · 1,046 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-graph-convolution-over-pruned-dependency/)
46. [**Adversarial Learning for Neural Dialogue Generation**Jiwei Li, Will Monroe, Tianlin Shi, et al.*2017 · 1,044 citations*](https://md.research.elamur.ai/free/en/papers/li-2017-adversarial-learning-neural-dialogue-generation/)
47. [**Better Word Representations with Recursive Neural Networks for Morphology**Thang Luong, Richard Socher, Christopher Manning*2013 · 1,017 citations*](https://md.research.elamur.ai/free/en/papers/luong-2013-better-word-representations-recursive-neural/)
48. [**Predicting Pragmatic Reasoning in Language Games**Michael C. Frank, Noah D. Goodman*2012 · 1,007 citations*](https://md.research.elamur.ai/free/en/papers/frank-2012-predicting-pragmatic-reasoning-language-games/)
49. [**Visualizing and Understanding Recurrent Networks**Andrej Karpathy, Justin Johnson, Li Fei-Fei*2015 · 939 citations*](https://md.research.elamur.ai/free/en/papers/karpathy-2015-visualizing-understanding-recurrent-networks/)
50. [**Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarization**Dave Van Veen, Cara Van Uden, Louis Blankemeier, et al.*2023 · 925 citations*](https://md.research.elamur.ai/free/en/papers/veen-2023-adapted-large-language-models-outperform/)
51. [**Leveraging Linguistic Structure For Open Domain Information Extraction**Gabor Angeli, Melvin Jose Johnson Premkumar, Christopher D. Manning*2015 · 921 citations*](https://md.research.elamur.ai/free/en/papers/angeli-2015-leveraging-linguistic-structure-open-domain/)
52. [**Visual7W: Grounded Question Answering in Images**Yuke Zhu, Oliver Groth, Michael Bernstein, et al.*2015 · 915 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2015-visual7w-grounded-question-answering-images/)
53. [**Universal Dependencies**Marie-Catherine de Marneffe, Christopher D. Manning, Joakim Nivre, et al.*2021 · 910 citations*](https://md.research.elamur.ai/free/en/papers/marneffe-2021-universal-dependencies-2/)
54. [**Grounded Compositional Semantics for Finding and Describing Images with Sentences**Richard Socher, Andrej Karpathy, Quoc V. Le, et al.*2014 · 909 citations*](https://md.research.elamur.ai/free/en/papers/socher-2014-grounded-compositional-semantics-finding-describing/)
55. [**Representing Text for Joint Embedding of Text and Knowledge Bases**Kristina Toutanova, Danqi Chen, Patrick Pantel, et al.*2015 · 904 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2015-representing-text-joint-embedding-text/)
56. [**Extracting Training Data from Large Language Models**Nicholas Carlini, Florian Tramer, Eric Wallace, et al.*2020 · 901 citations*](https://md.research.elamur.ai/free/en/papers/carlini-2020-extracting-training-data-large-language/)
57. [**Visualizing and Understanding Neural Models in NLP**Jiwei Li, Xinlei Chen, Eduard Hovy, et al.*2016 · 842 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-visualizing-understanding-neural-models-nlp/)
58. [**Is ChatGPT a General-Purpose Natural Language Processing Task Solver?**Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.*2023 · 818 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/)
59. [**Addressing the Rare Word Problem in Neural Machine Translation**Thang Luong, Ilya Sutskever, Quoc Le, et al.*2015 · 817 citations*](https://md.research.elamur.ai/free/en/papers/luong-2015-addressing-rare-word-problem-neural/)
60. [**ImageNet Large Scale Visual Recognition Challenge**Olga Russakovsky, Jia Deng, Hao Su, et al.*2014 · 816 citations*](https://md.research.elamur.ai/free/en/papers/russakovsky-2014-imagenet-large-scale-visual-recognition/)
61. [**SemEval-2014 Task 10: Multilingual Semantic Textual Similarity**Eneko Agirre, Carmen Banea, Claire Cardie, et al.*2014 · 783 citations*](https://md.research.elamur.ai/free/en/papers/agirre-2014-semeval-2014-task-10-multilingual/)
62. [**Can Large Language Models Transform Computational Social Science?**Caleb Ziems, William Held, Omar Shaikh, et al.*2023 · 776 citations*](https://md.research.elamur.ai/free/en/papers/ziems-2023-large-language-models-transform-computational/)
63. [**A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task**Danqi Chen, Jason Bolton, Christopher D. Manning*2016 · 689 citations*](https://md.research.elamur.ai/free/en/papers/chen-2016-thorough-examination-cnn-daily-mail/)
64. [**Semantic Parsing via Paraphrasing**Jonathan Berant, Percy Liang*2014 · 681 citations*](https://md.research.elamur.ai/free/en/papers/berant-2014-semantic-parsing-paraphrasing/)
65. [**Social Bias Frames: Reasoning about Social and Power Implications of Language**Maarten Sap, Saadia Gabriel, Lianhui Qin, et al.*2020 · 680 citations*](https://md.research.elamur.ai/free/en/papers/sap-2020-social-bias-frames-reasoning-about/)
66. [**Bilingual Word Embeddings for Phrase-Based Machine Translation**Will Y. Zou, Richard Socher, Daniel Cer, et al.*2013 · 680 citations*](https://md.research.elamur.ai/free/en/papers/zou-2013-bilingual-word-embeddings-phrase-based/)
67. [**Benchmarking Large Language Models for News Summarization**Tianyi Zhang, Faisal Ladhak, Esin Durmus, et al.*2024 · 663 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-benchmarking-large-language-models-news/)
68. [***SEM 2013 shared task: Semantic Textual Similarity**Eneko Agirre, Daniel Cer, Mona Diab, et al.*2013 · 658 citations*](https://md.research.elamur.ai/free/en/papers/agirre-2013-sem-2013-shared-task-semantic/)
69. [**Persistent Anti-Muslim Bias in Large Language Models**Abubakar Abid, Maheen Farooqi, James Zou*2021 · 640 citations*](https://md.research.elamur.ai/free/en/papers/abid-2021-persistent-anti-muslim-bias-large/)
70. [**The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages**Jan Hajič, Massimiliano Ciaramita, Richard Johansson, et al.*2009 · 631 citations*](https://md.research.elamur.ai/free/en/papers/hajic-2009-conll-2009-shared-task-syntactic/)
71. [**Universal Stanford dependencies: A cross-linguistic typology**Marie-Catherine de Marneffe, Timothy Dozat, Natalia Silveira, et al.*2014 · 626 citations*](https://md.research.elamur.ai/free/en/papers/marneffe-2014-universal-stanford-dependencies-cross-linguistic/)
72. [**CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies**Daniel Zeman, Martin Popel, Milan Straka, et al.*2017 · 604 citations*](https://md.research.elamur.ai/free/en/papers/zeman-2017-conll-2017-shared-task-multilingual/)
73. [**How Powerful are Graph Neural Networks?**Keyulu Xu, Weihua Hu, Jure Leskovec, et al.*2018 · 591 citations*](https://md.research.elamur.ai/free/en/papers/xu-2018-powerful-graph-neural-networks/)
74. [**s1: Simple test-time scaling**Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.*2025 · 584 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/)
75. [**Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules**Heeyoung Lee, Angel Chang, Yves Peirsman, et al.*2013 · 536 citations*](https://md.research.elamur.ai/free/en/papers/lee-2013-deterministic-coreference-resolution-based-entity/)
76. [**Evaluating Models' Local Decision Boundaries via Contrast Sets**Matt Gardner, Yoav Artzi, Victoria Basmov, et al.*2020 · 520 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2020-evaluating-models-local-decision-boundaries/)
77. [**FinQA: A Dataset of Numerical Reasoning over Financial Data**Zhiyu Chen, Wenhu Chen, Charese Smiley, et al.*2021 · 510 citations*](https://md.research.elamur.ai/free/en/papers/chen-2021-finqa-dataset-numerical-reasoning-over/)
78. [**Part-of-Speech Tagging from 97% to 100%: Is It Time for Some Linguistics?**Christopher D. Manning*2011 · 510 citations*](https://md.research.elamur.ai/free/en/papers/manning-2011-part-speech-tagging-97-100/)
79. [**A Structured Vector Space Model for Word Meaning in Context**Katrin Erk, Sebastian Padó*2008 · 508 citations*](https://md.research.elamur.ai/free/en/papers/erk-2008-structured-vector-space-model-word/)
80. [**Stanford's Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task**Heeyoung Lee, Yves Peirsman, Angel Chang, et al.*2011 · 506 citations*](https://md.research.elamur.ai/free/en/papers/lee-2011-stanford-s-multi-pass-sieve/)
81. [**Deep Visual-Semantic Alignments for Generating Image Descriptions**Andrej Karpathy, Li Fei-Fei*2014 · 493 citations*](https://md.research.elamur.ai/free/en/papers/karpathy-2014-deep-visual-semantic-alignments-generating/)
82. [**On building a more efficient grammar by exploiting types**Dan Flickinger*2000 · 492 citations*](https://md.research.elamur.ai/free/en/papers/flickinger-2000-building-more-efficient-grammar/)
83. [**Language Models are Multilingual Chain-of-Thought Reasoners**Freda Shi, Mirac Suzgun, Markus Freitag, et al.*2022 · 490 citations*](https://md.research.elamur.ai/free/en/papers/shi-2022-language-models-multilingual-chain-thought/)
84. [**Semi-Supervised Sequence Modeling with Cross-View Training**Kevin Clark, Minh-Thang Luong, Christopher D. Manning, et al.*2018 · 489 citations*](https://md.research.elamur.ai/free/en/papers/clark-2018-semi-supervised-sequence-modeling-cross/)
85. [**REPLUG: Retrieval-Augmented Black-Box Language Models**Weijia Shi, Sewon Min, Michihiro Yasunaga, et al.*2023 · 482 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-replug-retrieval-augmented-black-box/)
86. [**Universal Dependencies**Marie-Catherine de Marneffe, Christopher D. Manning, Joakim Nivre, et al.*2021 · 480 citations*](https://md.research.elamur.ai/free/en/papers/marneffe-2021-universal-dependencies/)
87. [**ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction**Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, et al.*2022 · 477 citations*](https://md.research.elamur.ai/free/en/papers/santhanam-2022-colbertv2-effective-efficient-retrieval-lightweight/)
88. [**A Simple and Effective Hierarchical Phrase Reordering Model**Michel Galley, Christopher D. Manning*2008 · 472 citations*](https://md.research.elamur.ai/free/en/papers/galley-2008-simple-effective-hierarchical-phrase-reordering/)
89. [**Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character Models**Minh-Thang Luong, Christopher D. Manning*2016 · 469 citations*](https://md.research.elamur.ai/free/en/papers/luong-2016-achieving-open-vocabulary-neural-machine/)
90. [**Evaluating Large Language Models in Theory of Mind Tasks**Michal Kosinski*2023 · 465 citations*](https://md.research.elamur.ai/free/en/papers/kosinski-2023-evaluating-large-language-models-theory/)
91. [**Deep Reinforcement Learning for Mention-Ranking Coreference Models**Kevin Clark, Christopher D. Manning*2016 · 461 citations*](https://md.research.elamur.ai/free/en/papers/clark-2016-deep-reinforcement-learning-mention-ranking/)
92. [**Denoising Diffusion Implicit Models**Jiaming Song, Chenlin Meng, Stefano Ermon*2020 · 460 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-denoising-diffusion-implicit-models/)
93. [**A Persona-Based Neural Conversation Model**Jiwei Li, Michel Galley, Chris Brockett, et al.*2016 · 456 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-persona-based-neural-conversation-model/)
94. [**Bilingual Word Representations with Monolingual Quality in Mind**Thang Luong, Hieu Pham, Christopher D. Manning*2015 · 453 citations*](https://md.research.elamur.ai/free/en/papers/luong-2015-bilingual-word-representations-monolingual-quality/)
95. [**LinkBERT: Pretraining Language Models with Document Links**Michihiro Yasunaga, Jure Leskovec, Percy Liang*2022 · 452 citations*](https://md.research.elamur.ai/free/en/papers/yasunaga-2022-linkbert-pretraining-language-models-document/)
96. [**Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets**Julia Kreutzer, Isaac Caswell, Lisa Wang, et al.*2021 · 447 citations*](https://md.research.elamur.ai/free/en/papers/kreutzer-2021-quality-glance-audit-web-crawled/)
97. [**A Multi-Pass Sieve for Coreference Resolution**Karthik Raghunathan, Heeyoung Lee, Sudarshan Rangarajan, et al.*2010 · 446 citations*](https://md.research.elamur.ai/free/en/papers/raghunathan-2010-multi-pass-sieve-coreference-resolution/)
98. [**Entity-Relation Extraction as Multi-Turn Question Answering**Xiaoya Li, Fan Yin, Zijun Sun, et al.*2019 · 437 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-entity-relation-extraction-as-multi/)
99. [**Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models**Matthew Dahl, Varun Magesh, Mirac Suzgun, et al.*2024 · 431 citations*](https://md.research.elamur.ai/free/en/papers/dahl-2024-large-legal-fictions-profiling-legal/)
100. [**Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora**William L. Hamilton, Kevin Clark, Jure Leskovec, et al.*2016 · 431 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2016-inducing-domain-specific-sentiment-lexicons/)

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