---
title: "University of Maryland, College Park — works"
description: "65 works by researchers of University of Maryland, College Park in our library, the most cited first."
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---
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# Works of University of Maryland, College Park

65 works · the most cited first · [← University of Maryland, College Park](https://md.research.elamur.ai/free/en/universities/university-of-maryland-college-park/)

1. [**A Study of Translation Edit Rate with Targeted Human Annotation**Matthew Snover, Bonnie Dorr, Rich Schwartz, et al.*2006 · 3,824 citations*](https://md.research.elamur.ai/free/en/papers/snover-2006-study-translation-edit-rate-targeted/)
2. [**Reading Tea Leaves: How Humans Interpret Topic Models**Jonathan Chang, Jordan Boyd-Graber, Sean Gerrish, et al.*2009 · 2,037 citations*](https://md.research.elamur.ai/free/en/papers/chang-2009-reading-tea-leaves-humans-interpret-topic/)
3. [**A Hierarchical Phrase-Based Model for Statistical Machine Translation**David Chiang*2005 · 1,683 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2005-hierarchical-phrase-based-model-statistical/)
4. [**Generating Natural Language Adversarial Examples**Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, et al.*2018 · 1,102 citations*](https://md.research.elamur.ai/free/en/papers/alzantot-2018-generating-natural-language-adversarial-examples/)
5. [**Deep Unordered Composition Rivals Syntactic Methods for Text Classification**Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, et al.*2015 · 914 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2015-deep-unordered-composition-rivals-syntactic/)
6. [**The Web as a Parallel Corpus**Philip Resnik, Noah A. Smith*2003 · 703 citations*](https://md.research.elamur.ai/free/en/papers/resnik-2003-web-as-parallel-corpus/)
7. [**A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)**Alane Suhr, Stephanie Zhou, Ally Zhang, et al.*2019 · 640 citations*](https://md.research.elamur.ai/free/en/papers/suhr-2019-corpus-reasoning-natural-language-grounded/)
8. [**Dear Sir or Madam, May I Introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer**Sudha Rao, Joel Tetreault*2018 · 581 citations*](https://md.research.elamur.ai/free/en/papers/rao-2018-dear-sir-or-madam-may/)
9. [**Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks**Hua He, Kevin Gimpel, Jimmy Lin*2015 · 447 citations*](https://md.research.elamur.ai/free/en/papers/he-2015-multi-perspective-sentence-similarity-modeling/)
10. [**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/)
11. [**FreeLB: Enhanced Adversarial Training for Natural Language Understanding**Chen Zhu, Yu Cheng, Zhe Gan, et al.*2019 · 443 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2019-freelb-enhanced-adversarial-training-natural/)
12. [**Generating Phrasal and Sentential Paraphrases: A Survey of Data-Driven Methods**Nitin Madnani, Bonnie J. Dorr*2010 · 425 citations*](https://md.research.elamur.ai/free/en/papers/madnani-2010-generating-phrasal-sentential-paraphrases-survey/)
13. [**Long Range Arena: A Benchmark for Efficient Transformers**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2020 · 396 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-long-range-arena-benchmark-efficient/)
14. [**A Watermark for Large Language Models**John Kirchenbauer, Jonas Geiping, Yuxin Wen, et al.*2023 · 374 citations*](https://md.research.elamur.ai/free/en/papers/kirchenbauer-2023-watermark-large-language-models/)
15. [**cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models**Chris Dyer, Adam Lopez, Juri Ganitkevitch, et al.*2010 · 372 citations*](https://md.research.elamur.ai/free/en/papers/dyer-2010-cdec-decoder-alignment-learning-framework/)
16. [**The ACL Anthology Reference Corpus: A Reference Dataset for Bibliographic Research in Computational Linguistics**Steven Bird, Robert Dale, Bonnie Dorr, et al.*2008 · 364 citations*](https://md.research.elamur.ai/free/en/papers/bird-2008-acl-anthology-reference-corpus-reference/)
17. [**The Media Frames Corpus: Annotations of Frames Across Issues**Dallas Card, Amber E. Boydstun, Justin H. Gross, et al.*2015 · 359 citations*](https://md.research.elamur.ai/free/en/papers/card-2015-media-frames-corpus-annotations-frames/)
18. [**Machine Translation Divergences: A Formal Description and Proposed Solution**Bonnie J. Dorr*1994 · 328 citations*](https://md.research.elamur.ai/free/en/papers/dorr-1994-machine-translation-divergences-formal-description/)
19. [**Search-based Neural Structured Learning for Sequential Question Answering**Mohit Iyyer, Wen-tau Yih, Ming-Wei Chang*2017 · 327 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2017-search-based-neural-structured-learning/)
20. [**HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models**Tianrui Guan, Fuxiao Liu, Xiyang Wu, et al.*2023 · 326 citations*](https://md.research.elamur.ai/free/en/papers/guan-2023-hallusionbench-advanced-diagnostic-suite-entangled/)
21. [**Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement**Hua He, Jimmy Lin*2016 · 293 citations*](https://md.research.elamur.ai/free/en/papers/he-2016-pairwise-word-interaction-modeling-deep/)
22. [**Expert, Crowdsourced, and Machine Assessment of Suicide Risk via Online Postings**Han-Chin Shing, Suraj Nair, Ayah Zirikly, et al.*2018 · 288 citations*](https://md.research.elamur.ai/free/en/papers/shing-2018-expert-crowdsourced-machine-assessment-suicide/)
23. [**POS Tagging of English-Hindi Code-Mixed Social Media Content**Yogarshi Vyas, Spandana Gella, Jatin Sharma, et al.*2014 · 273 citations*](https://md.research.elamur.ai/free/en/papers/vyas-2014-pos-tagging-english-hindi-code/)
24. [**A Continuously Growing Dataset of Sentential Paraphrases**Wuwei Lan, Siyu Qiu, Hua He, et al.*2017 · 265 citations*](https://md.research.elamur.ai/free/en/papers/lan-2017-continuously-growing-dataset-sentential-paraphrases/)
25. [**Can You Unpack That? Learning to Rewrite Questions-in-Context**Ahmed Elgohary, Denis Peskov, Jordan Boyd-Graber*2019 · 244 citations*](https://md.research.elamur.ai/free/en/papers/elgohary-2019-can-you-unpack-that-learning/)
26. [**In-context Examples Selection for Machine Translation**Sweta Agrawal, Chunting Zhou, Mike Lewis, et al.*2023 · 241 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/)
27. [**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/)
28. [**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/)
29. [**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/)
30. [**Baseline Defenses for Adversarial Attacks Against Aligned Language Models**Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.*2023 · 224 citations*](https://md.research.elamur.ai/free/en/papers/jain-2023-baseline-defenses-adversarial-attacks-against/)
31. [**Probing for semantic evidence of composition by means of simple classification tasks**Allyson Ettinger, Ahmed Elgohary, Philip Resnik*2016 · 217 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2016-probing-semantic-evidence-composition-means/)
32. [**AlpaGasus: Training A Better Alpaca with Fewer Data**Lichang Chen, Shiyang Li, Jun Yan, et al.*2023 · 214 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-alpagasus-training-better-alpaca-fewer/)
33. [**Improved Statistical Machine Translation Using Monolingually-Derived Paraphrases**Yuval Marton, Chris Callison-Burch, Philip Resnik*2009 · 213 citations*](https://md.research.elamur.ai/free/en/papers/marton-2009-improved-statistical-machine-translation-monolingually/)
34. [**Prompting GPT-3 To Be Reliable**Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.*2022 · 206 citations*](https://md.research.elamur.ai/free/en/papers/si-2022-prompting-gpt-3-reliable/)
35. [**End-to-End Slot Alignment and Recognition for Cross-Lingual NLU**Weijia Xu, Batool Haider, Saab Mansour*2020 · 194 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-end-end-slot-alignment-recognition/)
36. [**Refusal in Language Models Is Mediated by a Single Direction**Andy Arditi, Oscar Obeso, Aaquib Syed, et al.*2024 · 188 citations*](https://md.research.elamur.ai/free/en/papers/arditi-2024-refusal-language-models-mediated-single/)
37. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 187 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
38. [**Building a Shallow Arabic Morphological Analyser in One Day**Kareem Darwish*2002 · 183 citations*](https://md.research.elamur.ai/free/en/papers/darwish-2002-building-shallow-arabic-morphological-analyser/)
39. [**Soft Syntactic Constraints for Hierarchical Phrased-Based Translation**Yuval Marton, Philip Resnik*2008 · 183 citations*](https://md.research.elamur.ai/free/en/papers/marton-2008-soft-syntactic-constraints-hierarchical-phrased/)
40. [**Joshua: An Open Source Toolkit for Parsing-Based Machine Translation**Zhifei Li, Chris Callison-Burch, Chris Dyer, et al.*2009 · 163 citations*](https://md.research.elamur.ai/free/en/papers/li-2009-joshua-open-source-toolkit-parsing/)
41. [**CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims**Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian, et al.*2020 · 157 citations*](https://md.research.elamur.ai/free/en/papers/diggelmann-2020-climate-fever-dataset-verification-real/)
42. [**From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning**Ming Li, Yong Zhang, Zhitao Li, et al.*2023 · 157 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-quantity-quality-boosting-llm-performance/)
43. [**Toward Gender-Inclusive Coreference Resolution**Yang Trista Cao, Hal Daumé III*2020 · 125 citations*](https://md.research.elamur.ai/free/en/papers/cao-2020-gender-inclusive-coreference-resolution/)
44. [**Supervised and Unsupervised Methods in Employing Discourse Relations for Improving Opinion Polarity Classification**Swapna Somasundaran, Galileo Namata, Janyce Wiebe, et al.*2009 · 119 citations*](https://md.research.elamur.ai/free/en/papers/somasundaran-2009-supervised-unsupervised-methods-employing-discourse/)
45. [**Certifying LLM Safety against Adversarial Prompting**Aounon Kumar, Chirag Agarwal, Suraj Srinivas, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2023-certifying-llm-safety-against-adversarial/)
46. [**Olmo 3**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 109 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
47. [**SemEval-2016 Task 10: Detecting Minimal Semantic Units and their Meanings (DiMSUM)**Nathan Schneider, Dirk Hovy, Anders Johannsen, et al.*2016 · 100 citations*](https://md.research.elamur.ai/free/en/papers/schneider-2016-semeval-2016-task-10-detecting/)
48. [**Modality and Negation in SIMT Use of Modality and Negation in Semantically-Informed Syntactic MT**Kathryn Baker, Michael Bloodgood, Bonnie J. Dorr, et al.*2012 · 77 citations*](https://md.research.elamur.ai/free/en/papers/baker-2012-modality-negation-simt-use-modality/)
49. [**Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning Lifecycle***Yang Trista Cao, Hal Daumé III*2021 · 71 citations*](https://md.research.elamur.ai/free/en/papers/cao-2021-gender-inclusive-coreference-resolution-analysis/)
50. [**Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer**Eleftheria Briakou, Sweta Agrawal, Joel Tetreault, et al.*2021 · 49 citations*](https://md.research.elamur.ai/free/en/papers/briakou-2021-evaluating-evaluation-metrics-style-transfer/)
51. [**Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers**Anupam Guha, Mohit Iyyer, Danny Bouman, et al.*2015 · 39 citations*](https://md.research.elamur.ai/free/en/papers/guha-2015-removing-training-wheels-coreference-dataset/)
52. [**Adapting Coreference Resolution Models through Active Learning**Michelle Yuan, Patrick Xia, Chandler May, et al.*2022 · 35 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2022-adapting-coreference-resolution-models-through/)
53. [**Recognition of They/Them as Singular Personal Pronouns in Coreference Resolution**Connor Baumler, Rachel Rudinger*2022 · 19 citations*](https://md.research.elamur.ai/free/en/papers/baumler-2022-recognition-they-them-as-singular/)
54. [**Bridging Background Knowledge Gaps in Translation with Automatic Explicitation**HyoJung Han, Jordan Boyd-Graber, Marine Carpuat*2023 · 13 citations*](https://md.research.elamur.ai/free/en/papers/han-2023-bridging-background-knowledge-gaps-translation/)
55. [**Parameterization of the Interlingua in Machine Translation**Bonnie Dorr*1992 · 12 citations*](https://md.research.elamur.ai/free/en/papers/dorr-1992-parameterization-interlingua-machine-translation/)
56. [**Functional structure in the noun phrase: revisiting Hebrew nominals**Omer Preminger*2020 · 10 citations*](https://md.research.elamur.ai/free/en/papers/preminger-2020-functional-structure-noun-phrase-revisiting/)
57. [**How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability?**Neha Srikanth, Marine Carpuat, Rachel Rudinger*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/srikanth-2024-how-often-are-errors-natural/)
58. [**Toward compact monotonically compositional interlingua using lexical aspect**Bonnie J. Dorr, Mari Broman Olsen, Scott C. Thomas*1997 · 9 citations*](https://md.research.elamur.ai/free/en/papers/dorr-1997-compact-monotonically-compositional-interlingua-lexical/)
59. [**Error Correction for Arabic Dictionary Lookup**C. Anton Rytting, Paul Rodrigues, Tim Buckwalter, et al.*2010 · 7 citations*](https://md.research.elamur.ai/free/en/papers/rytting-2010-error-correction-arabic-dictionary-lookup/)
60. [**Bridging the Socioeconomic Gap in Education: A Hybrid AI and Human Annotation Approach**Nahed Abdelgaber, Labiba Jahan, Arham Vinit Doshi, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/abdelgaber-2025-bridging-socioeconomic-gap-education-hybrid/)
61. [**Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal**Sathvik Nair, Byung-Doh Oh*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/nair-2026-clozing-gap-exploring-why-language/)
62. [**Evaluating Native-Speaker Preferences on Machine Translation and Post-Edits for Five African Languages**Hiba El Oirghi, Tajuddeen Gwadabe, Marine Carpuat*2026*](https://md.research.elamur.ai/free/en/papers/oirghi-2026-evaluating-native-speaker-preferences-machine/)
63. [**Small Neural Networks as Models of Cross-Linguistic Speech Perception**Annika Shankwitz*2026*](https://md.research.elamur.ai/free/en/papers/shankwitz-2026-small-neural-networks-as-models/)
64. [**Frequency modulates structural choice in Turkish suspended affixation: a latent-process account**Utku Turk, Eva Neu, Özge Bakay, et al.*2026*](https://md.research.elamur.ai/free/en/papers/turk-2026-frequency-modulates-structural-choice-turkish/)
65. [**Quantifying the cross-linguistic effects of syncretism on agreement attraction**Utku Turk, Eva Neu*2026*](https://md.research.elamur.ai/free/en/papers/turk-2026-quantifying-cross-linguistic-effects-syncretism/)
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