Prof. Dr. Michael Strube

Group Leader Natural Language Processing

Contact

Phone: +49 6221 – 533 – 243

Fax: +49 6221 – 533 – 298

Group leader „Natural Language Processing“ at HITS “Honorarprofessor” at the Computational Linguistics Department at Heidelberg University

Research Interest

Linguistics:

Computational Linguistics:

Natural Language Processing:

Curriculum Vitae

2017-2018 Scientific Director at HITS
2017/18 Program Co-Chair Workshops on Ethics in NLP at ACL
2015 PC Co-Chair of the ACL’s flagship conference ACL-IJCNLP ’15 in Beijing, China, July 26-31, 2015
Since 2010 “Honorarprofessor” in the Computational Linguistics Department at the University of Heidelberg
Since 2003 Member of the EML Research, now HITS
2000-2003 Member of the EML European Media Laboratory
1997-1999 PostDoc at the Institute for Research in Cognitive Science at the University of Pennsylvania, Philadelphia, US
1996 PhD at the University of Freiburg, Germany

2023

2022

  • Zhao W, Eger S (2022). Constrained density matching and modeling for cross-lingual alignment of contextualized representations, Proceedings of Machine Learning Research, 2022. Asian Conference on Machine Leaning, Hyderabad, India, 12-14 December 2022 1598
  • Yu J, Khosla S, Manuvinakurike R, Levin L, Ng V, Poesio M, Strube M, Rosé C (2022). Proceedings of the CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue, Proceedings of the CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue, Gyeongju, Republic of Korea, October 2022 1590
  • Yu J, Khosla S, Manuvinakurike R, Levin L, Ng V, Poesio M, Strube M, Rosé C (2022). The CODI-CRAC 2022 shared task on anaphora, bridging, and discourse deixis in dialogue, Proceedings of the CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue, Gyeongju, Repbulic of Korea, October 2022, pp. 1–14 1591
  • Braud C, Hardmeier C, Li JJ, Loaciga S, Strube M, Zeldes A (2022). Proceedings of the 3rd Workshop on Computational Approaches to Discourse, Proceedings of the 3rd Workshop on Computational Approaches to Discourse, Gyeongju, Republic of Korea, October 2022 1589
  • Chai H, Moosavi NS, Gurevych I, Strube M (2022). Evaluating coreference resolvers on community-based question answering: From rule-based to state of the art, Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference, Gyeongju, Republic of Korea, 16–17 Octrober, 2022, pp.61–73 1592
  • Liang S, Kades K, Fink M, Full P, Weber T, Kleesiek J, Strube M, Maier-Hein K (2022). Fine-tuning BERT Models for Summarizing German Radiology Findings, Proceedings of the 4th Clinical Natural Language Processing Workshop, Seattle, Washington, July 2022 1498
  • Chai H, Strube M (2022). Incorporating Centering Theory into Neural Coreference Resolution, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Seattle, Washington, July 2022 1496
  • Jeon S, Strube M (2022). Entity-based Neural Local Coherence Modeling, In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL). Dublin, Ireland, May 2022 1471
  • Zhao W, Mathews K, Chai H (2022). Improving coreference resolution with word formation, Book of Abstracts of the Symposium on Word Formation and Discourse Structure, Leipzig, Germany, May 2022, pp.16–17 1593
  • Müller M (2022). A proposal for explicit word formation annotation in discourse corpora, Book of Abstracts of the Symposium on Word Formation and Discourse Structure, Leipzig, Germany, May 2022, pp14–15 1594
  • Srivastava A, Rastogi A, Rao A, Shoeb AAM, Abid A, Fisch A, Brown AR, Santoro A, Gupta A, Garriga-Alonso A, Kluska A, Lewkowycz A, Agarwal A, Power A, Ray A, Warstadt A, Kocurek AW, Safaya A, Tazarv A, Xiang A, Parrish A, Nie A, Hussain A, Askell A, Dsouza A, Slone A, Rahane A, Iyer AS, Andreassen A, Madotto A, Santilli A, Stuhlmüller A, Dai A, La A, Lampinen A, Zou A, Jiang A, Chen A, Vuong A, Gupta A, Gottardi A, Norelli A, Venkatesh A, Gholamidavoodi A, Tabassum A, Menezes A, Kirubarajan A, Mullokandov A, Sabharwal A, Herrick A, Efrat A, Erdem A, Karakaş A, Roberts BR, Loe BS, Zoph B, Bojanowski B, Özyurt B, Hedayatnia B, Neyshabur B, Inden B, Stein B, Ekmekci B, Lin BY, Howald B, Diao C, Dour C, Stinson C, Argueta C, Ramírez CF, Singh C, Rathkopf C, Meng C, Baral C, Wu C, Callison-Burch C, Waites C, Voigt C, Manning CD, Potts C, Ramirez C, Rivera CE, Siro C, Raffel C, Ashcraft C, Garbacea C, Sileo D, Garrette D, Hendrycks D, Kilman D, Roth D, Freeman D, Khashabi D, Levy D, González DM, Perszyk D, Hernandez D, Chen D, Ippolito D, Gilboa D, Dohan D, Drakard D, Jurgens D, Datta D, Ganguli D, Emelin D, Kleyko D, Yuret D, Chen D, Tam D, Hupkes D, Misra D, Buzan D, Mollo DC, Yang D, Lee D, Shutova E, Cubuk ED, Segal E, Hagerman E, Barnes E, Donoway E, Pavlick E, Rodola E, Lam E, Chu E, Tang E, Erdem E, Chang E, Chi EA, Dyer E, Jerzak E, Kim E, Manyasi EE, Zheltonozhskii E, Xia F, Siar F, Martínez-Plumed F, Happé F, Chollet F, Rong F, Mishra G, Winata GI, Melo Gd, Kruszewski G, Parascandolo G, Mariani G, Wang G, Jaimovitch-López G, Betz G, Gur-Ari G, Galijasevic H, Kim H, Rashkin H, Hajishirzi H, Mehta H, Bogar H, Shevlin H, Schütze H, Yakura H, Zhang H, Wong HM, Ng I, Noble I, Jumelet J, Geissinger J, Kernion J, Hilton J, Lee J, Fisac JF, Simon JB, Koppel J, Zheng J, Zou J, Kocoń J, Thompson J, Kaplan J, Radom J, Sohl-Dickstein J, Phang J, Wei J, Yosinski J, Novikova J, Bosscher J, Marsh J, Kim J, Taal J, Engel J, Alabi J, Xu J, Song J, Tang J, Waweru J, Burden J, Miller J, Balis JU, Berant J, Frohberg J, Rozen J, Hernandez-Orallo J, Boudeman J, Jones J, Tenenbaum JB, Rule JS, Chua J, Kanclerz K, Livescu K, Krauth K, Gopalakrishnan K, Ignatyeva K, Markert K, Dhole KD, Gimpel K, Omondi K, Mathewson K, Chiafullo K, Shkaruta K, Shridhar K, McDonell K, Richardson K, Reynolds L, Gao L, Zhang L, Dugan L, Qin L, Contreras-Ochando L, Morency L, Moschella L, Lam L, Noble L, Schmidt L, He L, Colón LO, Metz L, Şenel LK, Bosma M, Sap M, Hoeve Mt, Farooqi M, Faruqui M, Mazeika M, Baturan M, Marelli M, Maru M, Quintana MJR, Tolkiehn M, Giulianelli M, Lewis M, Potthast M, Leavitt ML, Hagen M, Schubert M, Baitemirova MO, Arnaud M, McElrath M, Yee MA, Cohen M, Gu M, Ivanitskiy M, Starritt M, Strube M, Swędrowski M, Bevilacqua M, Yasunaga M, Kale M, Cain M, Xu M, Suzgun M, Tiwari M, Bansal M, Aminnaseri M, Geva M, Gheini M, T MV, Peng N, Chi N, Lee N, Krakover NG, Cameron N, Roberts N, Doiron N, Nangia N, Deckers N, Muennighoff N, Keskar NS, Iyer NS, Constant N, Fiedel N, Wen N, Zhang O, Agha O, Elbaghdadi O, Levy O, Evans O, Casares PAM, Doshi P, Fung P, Liang PP, Vicol P, Alipoormolabashi P, Liao P, Liang P, Chang P, Eckersley P, Htut PM, Hwang P, Miłkowski P, Patil P, Pezeshkpour P, Oli P, Mei Q, Lyu Q, Chen Q, Banjade R, Rudolph RE, Gabriel R, Habacker R, Delgado RR, Millière R, Garg R, Barnes R, Saurous RA, Arakawa R, Raymaekers R, Frank R, Sikand R, Novak R, Sitelew R, LeBras R, Liu R, Jacobs R, Zhang R, Salakhutdinov R, Chi R, Lee R, Stovall R, Teehan R, Yang R, Singh S, Mohammad SM, Anand S, Dillavou S, Shleifer S, Wiseman S, Gruetter S, Bowman SR, Schoenholz SS, Han S, Kwatra S, Rous SA, Ghazarian S, Ghosh S, Casey S, Bischoff S, Gehrmann S, Schuster S, Sadeghi S, Hamdan S, Zhou S, Srivastava S, Shi S, Singh S, Asaadi S, Gu SS, Pachchigar S, Toshniwal S, Upadhyay S, Shyamolima , Debnath , Shakeri S, Thormeyer S, Melzi S, Reddy S, Makini SP, Lee S, Torene S, Hatwar S, Dehaene S, Divic S, Ermon S, Biderman S, Lin S, Prasad S, Piantadosi ST, Shieber SM, Misherghi S, Kiritchenko S, Mishra S, Linzen T, Schuster T, Li T, Yu T, Ali T, Hashimoto T, Wu T, Desbordes T, Rothschild T, Phan T, Wang T, Nkinyili T, Schick T, Kornev T, Telleen-Lawton T, Tunduny T, Gerstenberg T, Chang T, Neeraj T, Khot T, Shultz T, Shaham U, Misra V, Demberg V, Nyamai V, Raunak V, Ramasesh V, Prabhu VU, Padmakumar V, Srikumar V, Fedus W, Saunders W, Zhang W, Vossen W, Ren X, Tong X, Zhao X, Wu X, Shen X, Yaghoobzadeh Y, Lakretz Y, Song Y, Bahri Y, Choi Y, Yang Y, Hao Y, Chen Y, Belinkov Y, Hou Y, Hou Y, Bai Y, Seid Z, Zhao Z, Wang Z, Wang ZJ, Wang Z, Wu Z (2022). Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models, https://arxiv.org/abs/2206.04615 1499

2021

2020

2019

2018

  • Hou Y, Markert K, Strube M (2018). Unrestricted bridging resolution, Computational Linguistics 44(2):237-284 395
  • Heinzerling B, Strube M (2018). BPEmb: Tokenization-free pre-trained subword embeddings in 275 languages, In Proceedings of the 11th International Conference on Language Resources and Evaluation, Miyazaki, Japan, 7–12 May 2018 394
  • Kirilin A, Strube M (2018). Exploiting a speaker’s credibility to detect fake news, In Workshop on Data Science, Journalism and Media, London, UK, 20 August 2018 396
  • Mesgar M, Strube M (2018). A neural local coherence model for text quality assessment, In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, 31 October – 4 November 2018, pp. 4328-4339 397
  • Müller M, Strube M (2018). Transparent, efficient, and robust word embedding access with WOMBAT, In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, Santa Fé, New Mexico, 20–26 August 2018, pp. 53-57 400
  • Moosavi NS, Strube M (2018). Using linguistic features to improve generalization in neural coreference resolvers, In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, 31 October – 4 November 2018, pp. 193-203 401
  • Suter J, Strube M (2018). Extending and exploiting the entity graph for analysis, classification and visualization of German texts, In Proceedings of the 14th Conference on Natural Language Processing (KONVENS), Vienna, Austria, 17–19 September 2018, pp. 136-140 403
  • Alfano M, Hovy D, Mitchell M, Strube M (2018). Proceedings of the 2nd ACL Workshop on Ethics in Natural Language Processing, New Orleans, Louis., 5 June 2018, http://aclweb.org/anthology/W18-0800.pdf 406

2017

  • Born L, Mesgar M, Strube M (2017). Using a graph-based coherence model in document-Level machine translation, In Proceedings of the 3rd Workshop on Discourse in Machine Translation, Copenhagen, Denmark, 8 September 2017, pp. 26-35 278
  • Heinzerling B, Strube M, Lin C (2017). Trust, but verify! Better entity linking through automatic verification, In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, Valencia, Spain, 3–7 April 2017, pp. 828-838 279
  • Heinzerling B, Moosavi NS, Strube M (2017). Revisiting selectional preferences for coreference resolution, In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Copenhagen, Denmark, 7–11 September 2017, pp. 1343-1350 280
  • Hovy D, Spruit S, Mitchell M, Bender EM, Strube M, Wallach H (2017). Proceedings of the First ACL Workshop on Ethics in Natural Language Processing, Valencia, Spain, 4 April 2017, http://www.aclweb.org/anthology/W17-16.pdf 281
  • Judea A, Strube M (2017). Event argument identification on dependency graphs with bidirectional LSTMs, In Proceedings of the 8th International Joint Conference on Natural Language Processing, Taipei, Taiwan, 27 November – 1 December 2017, pp. 822-831 282
  • Kurohashi S, Strube M (2017). Proceedings of the IJCNLP 2017, Tutorial Abstracts, Taipei, Taiwan, 27 November 2017, http://www.aclweb.org/anthology/I17-5.pdf 283
  • Moosavi NS, Strube M (2017). Use generalized representations, but do not forget surface features, In Proceedings of the 2nd Workshop on Coreference Resolution Beyond OntoNotes, Valencia, Spain, 4 April 2017, pp. 1-7 284
  • Moosavi NS, Strube M (2017). Lexical features in coreference resolution: To be used with caution, In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (vol. 2: Short Papers), Vancouver, B.C., Canada, 30 July –4 August 2017 285

2016

  • Resch B, Summa A, Zeile P, Strube M (2016). Citizen-centric urban planning through extracting emotion information from Twitter in an interdisciplinary space-time-linguistics algorithm, UP 1(2):114 196
  • Heinzerling B, Judea A, Strube M (2016). HITS at TAC KBP 2015: Entity discovery and linking, and event nugget detection, In Proceedings of the Text Analysis Conference, National Institute of Standards and Technology, Gaithersburg, Maryland, USA, 16–17 November 2015 189
  • Judea A, Strube M (2016). Incremental global event extraction, In Proceedings of the 26th International Conference on Computational Linguistics, Osaka, Japan, 11–16 December 2016, pp. 2279-2289 190
  • Mesgar M, Strube M (2016). Lexical coherence graph modeling using word embeddings, In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, Cal., 12–17 June 2016, pp. 1414-1423 191
  • Moosavi NS, Strube M (2016). Search space pruning: A simple solution for better coreference resolvers, In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, Cal., 12–17 June 2016, pp. 1005-1011 192
  • Moosavi NS, Strube M (2016). Which coreference evaluation metric do you trust? A proposal for a link-based entity aware metric, In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (vol. 1: Long Papers), Berlin, Germany, 7–12 August 2016, pp. 632-642 193
  • Parveen D, Mesgar M, Strube M (2016). Generating coherent summaries of scientific articles using coherence patterns, In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, Austin, Tex., 1–5 November 2016, pp. 772-783 194
  • Remse M, Mesgar M, Strube M (2016). Feature-rich error detection in scientific writing using logistic regression, In Proceedings of the 11th Workshop on Innovative Use of NLP for Building Educational Applications, San Diego, Cal., 16 June 2016, pp. 162-171 195
  • Summa A, Resch B, Strube M (2016). Microblog emotion classification by computing similarity in text, time, and space, In Proceedings of the Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media, Osaka, Japan, 12 December 2016, pp. 153-162 197


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