---
title: "University of Illinois Urbana-Champaign — works"
description: "76 works by researchers of University of Illinois Urbana-Champaign in our library, the most cited first."
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# Works of University of Illinois Urbana-Champaign

76 works · the most cited first · [← University of Illinois Urbana-Champaign](https://md.research.elamur.ai/free/en/universities/university-of-illinois-urbana-champaign/)

1. [**SciPy 1.0 — Fundamental Algorithms for Scientific Computing in Python**Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, et al.*2019 · 38,317 citations*](https://md.research.elamur.ai/free/en/papers/virtanen-2019-scipy-1-0-fundamental-algorithms/)
2. [**Word Representations: A Simple and General Method for Semi-Supervised Learning**Joseph Turian, Lev-Arie Ratinov, Yoshua Bengio*2010 · 2,421 citations*](https://md.research.elamur.ai/free/en/papers/turian-2010-word-representations-simple-general-method/)
3. [**Design Challenges and Misconceptions in Named Entity Recognition**Lev Ratinov, Dan Roth*2009 · 1,836 citations*](https://md.research.elamur.ai/free/en/papers/ratinov-2009-design-challenges-misconceptions-named-entity/)
4. [**Learning Question Classifiers**Xin Li, Dan Roth*2002 · 1,645 citations*](https://md.research.elamur.ai/free/en/papers/li-2002-learning-question-classifiers/)
5. [**Instance Weighting for Domain Adaptation in NLP**Jing Jiang, ChengXiang Zhai*2007 · 870 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2007-instance-weighting-domain-adaptation-nlp/)
6. [**Towards Reasoning in Large Language Models: A Survey**Jie Huang, Kevin Chen-Chuan Chang*2023 · 775 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/)
7. [**A Joint Model of Text and Aspect Ratings for Sentiment Summarization**Ivan Titov, Ryan McDonald*2008 · 729 citations*](https://md.research.elamur.ai/free/en/papers/titov-2008-joint-model-text-aspect-ratings/)
8. [**ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge**Yunxiang Li, Zihan Li, Kai Zhang, et al.*2023 · 640 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-chatdoctor-medical-chat-model-fine/)
9. [**A Linear Programming Formulation for Global Inference in Natural Language Tasks**Dan Roth, Wen-tau Yih*2004 · 636 citations*](https://md.research.elamur.ai/free/en/papers/roth-2004-linear-programming-formulation-global-inference/)
10. [**Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions**Kavita Ganesan, ChengXiang Zhai, Jiawei Han*2010 · 608 citations*](https://md.research.elamur.ai/free/en/papers/ganesan-2010-opinosis-graph-based-approach-abstractive/)
11. [**A Joint Neural Model for Information Extraction with Global Features**Ying Lin, Heng Ji, Fei Huang, et al.*2020 · 600 citations*](https://md.research.elamur.ai/free/en/papers/lin-2020-joint-neural-model-information-extraction/)
12. [**Solving General Arithmetic Word Problems**Subhro Roy, Dan Roth*2015 · 580 citations*](https://md.research.elamur.ai/free/en/papers/roy-2015-solving-general-arithmetic-word-problems/)
13. [**Collecting Image Annotations Using Amazon's Mechanical Turk**Cyrus Rashtchian, Peter Young, Micah Hodosh, et al.*2010 · 562 citations*](https://md.research.elamur.ai/free/en/papers/rashtchian-2010-collecting-image-annotations-amazon-s/)
14. [**Large Language Models Can Self-Improve**Jiaxin Huang, Shixiang Gu, Le Hou, et al.*2023 · 560 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-can-self/)
15. [**TextBugger: Generating Adversarial Text Against Real-world Applications**Jinfeng Li, Shouling Ji, Tianyu Du, et al.*2018 · 541 citations*](https://md.research.elamur.ai/free/en/papers/li-2018-textbugger-generating-adversarial-text-against/)
16. [**The Importance of Syntactic Parsing and Inference in Semantic Role Labeling**Vasin Punyakanok, Dan Roth, Wen-tau Yih*2008 · 538 citations*](https://md.research.elamur.ai/free/en/papers/punyakanok-2008-importance-syntactic-parsing-inference-semantic/)
17. [**Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning**Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, et al.*2019 · 536 citations*](https://md.research.elamur.ai/free/en/papers/huang-2019-cosmos-qa-machine-reading-comprehension/)
18. [**Regularizing Neural Networks by Penalizing Confident Output Distributions**Gabriel Pereyra, George Tucker, Jan Chorowski, et al.*2017 · 482 citations*](https://md.research.elamur.ai/free/en/papers/pereyra-2017-regularizing-neural-networks-penalizing-confident/)
19. [**Measuring Coding Challenge Competence With APPS**Dan Hendrycks, Steven Basart, Saurav Kadavath, et al.*2021 · 438 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-measuring-coding-challenge-competence-apps/)
20. [**Document-Level Event Argument Extraction by Conditional Generation**Sha Li, Heng Ji, Jiawei Han*2021 · 432 citations*](https://md.research.elamur.ai/free/en/papers/li-2021-document-level-event-argument-extraction/)
21. [**WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia**Holger Schwenk, Vishrav Chaudhary, Shuo Sun, et al.*2019 · 424 citations*](https://md.research.elamur.ai/free/en/papers/schwenk-2019-wikimatrix-mining-135m-parallel-sentences/)
22. [**Empower Sequence Labeling with Task-Aware Neural Language Model**Liyuan Liu, Jingbo Shang, Frank F. Xu, et al.*2017 · 419 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-empower-sequence-labeling-task-aware/)
23. [**UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models**Tianbao Xie, Chen Henry Wu, Peng Shi, et al.*2022 · 405 citations*](https://md.research.elamur.ai/free/en/papers/xie-2022-unifiedskg-unifying-multi-tasking-structured/)
24. [**Large Language Models Cannot Self-Correct Reasoning Yet**Jie Huang, Xinyun Chen, Swaroop Mishra, et al.*2023 · 396 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-cannot-self/)
25. [**Tool Learning with Foundation Models**Yujia Qin, Shengding Hu, Yankai Lin, et al.*2023 · 376 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-tool-learning-foundation-models/)
26. [**From Paraphrase Database to Compositional Paraphrase Model and Back**John Wieting, Mohit Bansal, Kevin Gimpel, et al.*2015 · 375 citations*](https://md.research.elamur.ai/free/en/papers/wieting-2015-paraphrase-database-compositional-paraphrase-model/)
27. [**Understanding the Value of Features for Coreference Resolution**Eric Bengtson, Dan Roth*2008 · 352 citations*](https://md.research.elamur.ai/free/en/papers/bengtson-2008-understanding-value-features-coreference-resolution/)
28. [**Efficient Attentions for Long Document Summarization**Luyang Huang, Shuyang Cao, Nikolaus Parulian, et al.*2021 · 334 citations*](https://md.research.elamur.ai/free/en/papers/huang-2021-efficient-attentions-long-document-summarization/)
29. [**A massively parallel corpus: the Bible in 100 languages**Christos Christodouloupoulos, Mark J. Steedman*2014 · 317 citations*](https://md.research.elamur.ai/free/en/papers/christodouloupoulos-2014-massively-parallel-corpus-bible-100/)
30. [**Learning Named Entity Tagger using Domain-Specific Dictionary**Jingbo Shang, Liyuan Liu, Xiaotao Gu, et al.*2018 · 301 citations*](https://md.research.elamur.ai/free/en/papers/shang-2018-learning-named-entity-tagger-domain/)
31. [**Multi-step Jailbreaking Privacy Attacks on ChatGPT**Haoran Li, Dadi Guo, Wei Fan, et al.*2023 · 298 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-multi-step-jailbreaking-privacy-attacks/)
32. [**A Bayesian Mixed Effects Model of Literary Character**David Bamman, Ted Underwood, Noah A. Smith*2014 · 285 citations*](https://md.research.elamur.ai/free/en/papers/bamman-2014-bayesian-mixed-effects-model-literary/)
33. [**emrQA: A Large Corpus for Question Answering on Electronic Medical Records**Anusri Pampari, Preethi Raghavan, Jennifer Liang, et al.*2018 · 285 citations*](https://md.research.elamur.ai/free/en/papers/pampari-2018-emrqa-large-corpus-question-answering/)
34. [**Text Classification Using Label Names Only: A Language Model Self-Training Approach**Yu Meng, Yunyi Zhang, Jiaxin Huang, et al.*2020 · 274 citations*](https://md.research.elamur.ai/free/en/papers/meng-2020-text-classification-label-names-only/)
35. [**Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads**Tianle Cai, Yuhong Li, Zhengyang Geng, et al.*2024 · 271 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-medusa-simple-llm-inference-acceleration/)
36. [**Factuality Challenges in the Era of Large Language Models**Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.*2023 · 241 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2023-factuality-challenges-era-large-language/)
37. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
38. [**TrustLLM: Trustworthiness in Large Language Models**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
39. [**An Unsupervised Sentence Embedding Method by Mutual Information Maximization**Yan Zhang, Ruidan He, Zuozhu Liu, et al.*2020 · 213 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2020-unsupervised-sentence-embedding-method-mutual/)
40. [**Generating Training Data with Language Models: Towards Zero-Shot Language Understanding**Yu Meng, Jiaxin Huang, Yu Zhang, et al.*2022 · 206 citations*](https://md.research.elamur.ai/free/en/papers/meng-2022-generating-training-data-language-models/)
41. [**RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models**Cheng Niu, Yuanhao Wu, Juno Zhu, et al.*2024 · 204 citations*](https://md.research.elamur.ai/free/en/papers/niu-2024-ragtruth-hallucination-corpus-developing-trustworthy/)
42. [**Towards a Unified Multi-Dimensional Evaluator for Text Generation**Ming Zhong, Yang Liu, Da Yin, et al.*2022 · 204 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2022-unified-multi-dimensional-evaluator-text/)
43. [**Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs**Suyu Ge, Yunan Zhang, Liyuan Liu, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/ge-2023-model-tells-discard-adaptive-kv/)
44. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 196 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/)
45. [**Event Detection and Co-reference with Minimal Supervision**Haoruo Peng, Yangqiu Song, Dan Roth*2016 · 180 citations*](https://md.research.elamur.ai/free/en/papers/peng-2016-event-detection-co-reference-minimal/)
46. [**Aligning Large Multimodal Models with Factually Augmented RLHF**Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-aligning-large-multimodal-models-factually/)
47. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
48. [**L-Eval: Instituting Standardized Evaluation for Long Context Language Models**Chenxin An, Shansan Gong, Ming Zhong, et al.*2023 · 159 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-l-eval-instituting-standardized-evaluation/)
49. [**When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/)
50. [**Generation-Augmented Retrieval for Open-domain Question Answering**Yuning Mao, Pengcheng He, Xiaodong Liu, et al.*2020 · 150 citations*](https://md.research.elamur.ai/free/en/papers/mao-2020-generation-augmented-retrieval-open-domain/)
51. [**Process Reinforcement through Implicit Rewards**Ganqu Cui, Lifan Yuan, Zefan Wang, et al.*2025 · 147 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-process-reinforcement-through-implicit-rewards/)
52. [**Executable Code Actions Elicit Better LLM Agents**Xingyao Wang, Yangyi Chen, Lifan Yuan, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-executable-code-actions-elicit-better/)
53. [**Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts**Haoxiang Wang, Wei Xiong, Tengyang Xie, et al.*2024 · 142 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-interpretable-preferences-multi-objective-reward/)
54. [**Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration**Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al.*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-unleashing-emergent-cognitive-synergy-large/)
55. [**MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback**Xingyao Wang, Zihan Wang, Jiateng Liu, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mint-evaluating-llms-multi-turn/)
56. [**Unit Dependency Graph and its Application to Arithmetic Word Problem Solving**Subhro Roy, Dan Roth*2017 · 130 citations*](https://md.research.elamur.ai/free/en/papers/roy-2017-unit-dependency-graph-arithmetic/)
57. [**Solving Hard Coreference Problems**Haoruo Peng, Daniel Khashabi, Dan Roth*2015 · 118 citations*](https://md.research.elamur.ai/free/en/papers/peng-2015-solving-hard-coreference-problems/)
58. [**Data Engineering for Scaling Language Models to 128K Context**Yao Fu, Rameswar Panda, Xinyao Niu, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-data-engineering-scaling-language-models/)
59. [**A Constrained Latent Variable Model for Coreference Resolution**Kai-Wei Chang, Rajhans Samdani, Dan Roth*2013 · 80 citations*](https://md.research.elamur.ai/free/en/papers/chang-2013-constrained-latent-variable-model-coreference/)
60. [**Discourse Coherence in the Wild: A Dataset, Evaluation and Methods**Alice Lai, Joel Tetreault*2018 · 79 citations*](https://md.research.elamur.ai/free/en/papers/lai-2018-discourse-coherence-wild-dataset-evaluation/)
61. [**A Joint Framework for Coreference Resolution and Mention Head Detection**Haoruo Peng, Kai-Wei Chang, Dan Roth*2015 · 75 citations*](https://md.research.elamur.ai/free/en/papers/peng-2015-joint-framework-coreference-resolution-mention/)
62. [**Idiomatic Expression Identification using Semantic Compatibility**Ziheng Zeng, Suma Bhat*2021 · 75 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2021-idiomatic-expression-identification-semantic-compatibility/)
63. [**Learning-based Multi-Sieve Co-reference Resolution with Knowledge**Lev Ratinov, Dan Roth*2012 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ratinov-2012-learning-based-multi-sieve-co/)
64. [**Unsupervised Grammar Induction with Depth-bounded PCFG**Lifeng Jin, Finale Doshi-Velez, Timothy Miller, et al.*2018 · 55 citations*](https://md.research.elamur.ai/free/en/papers/jin-2018-unsupervised-grammar-induction-depth-bounded/)
65. [**Inference Protocols for Coreference Resolution**Kai-Wei Chang, Rajhans Samdani, Alla Rozovskaya, et al.*2011 · 50 citations*](https://md.research.elamur.ai/free/en/papers/chang-2011-inference-protocols-coreference-resolution/)
66. [**A Context-Dependent Gated Module for Incorporating Symbolic Semantics into Event Coreference Resolution**Tuan Lai, Heng Ji, Trung Bui, et al.*2021 · 48 citations*](https://md.research.elamur.ai/free/en/papers/lai-2021-context-dependent-gated-module-incorporating/)
67. [**Revisiting the Evaluation for Cross Document Event Coreference**Shyam Upadhyay, Nitish Gupta, Christos Christodoulopoulos, et al.*2016 · 30 citations*](https://md.research.elamur.ai/free/en/papers/upadhyay-2016-revisiting-evaluation-cross-document-event/)
68. [**Identifying Semitic Roots: Machine Learning with Linguistic Constraints**Ezra Daya, Dan Roth, Shuly Wintner*2008 · 25 citations*](https://md.research.elamur.ai/free/en/papers/daya-2008-identifying-semitic-roots-machine-learning/)
69. [**Learning Hebrew Roots: Machine Learning with Linguistic Constraints**Ezra Daya, Dan Roth, Shuly Wintner*2004 · 23 citations*](https://md.research.elamur.ai/free/en/papers/daya-2004-learning-hebrew-roots-machine-learning/)
70. [**IEKG: A Commonsense Knowledge Graph for Idiomatic Expressions**Ziheng Zeng, Kellen Tan Cheng, Srihari Venkat Nanniyur, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2023-iekg-commonsense-knowledge-graph-idiomatic/)
71. [**Constrained Sequence-to-sequence Semitic Root Extraction for Enriching Word Embeddings**Ahmed El-Kishky, Xingyu Fu, Aseel Addawood, et al.*2019 · 6 citations*](https://md.research.elamur.ai/free/en/papers/kishky-2019-constrained-sequence-sequence-semitic-root/)
72. [**Unsupervised Construction of a Lexicon and a Repository of Variation Patterns for Arabic Modal Multiword Expressions**Rania Al-Sabbagh, Roxana Girju, Jana Diesner*2014 · 6 citations*](https://md.research.elamur.ai/free/en/papers/sabbagh-2014-unsupervised-construction-lexicon-repository-variation/)
73. [**No Context Needed: Contextual Quandary In Idiomatic Reasoning With Pre-Trained Language Models**Kellen Tan Cheng, Suma Bhat*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-no-context-needed-contextual-quandary/)
74. [**Some Dialects Are More Equal Than Others: Non-Prestigious Arabic Dialectal Bias in LLMs**Mai Mohamed Eida, Ryan Dolan, Paul de Nijs, et al.*2026*](https://md.research.elamur.ai/free/en/papers/eida-2026-some-dialects-more-equal-than/)
75. [**Coordination of unmatched clause types and dynamic look-ahead**Peter Lasersohn*2026*](https://md.research.elamur.ai/free/en/papers/lasersohn-2026-coordination-unmatched-clause-types-dynamic/)
76. [**GBC: Gradient-Based Connections for Optimizing Multi-Agent Systems**Xiaocheng Yang, Abdulrahman Alrabah, Dilek Hakkani-Tür, et al.*2026*](https://md.research.elamur.ai/free/en/papers/yang-2026-gbc-gradient-based-connections-optimizing/)
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