For best experience please turn on javascript and use a modern browser!
You are using a browser that is no longer supported by Microsoft. Please upgrade your browser. The site may not present itself correctly if you continue browsing.

Prof. dr. C. (Christof) Monz

Faculty of Science
Informatics Institute

Visiting address
  • Science Park 904
  • Room number: C3.231
Postal address
  • Postbus 94323
    1090 GH Amsterdam
  • Publications

    2023

    • Araabi, A., Niculae, V., & Monz, C. (2023). Joint Dropout: Improving Generalizability in Low-Resource Neural Machine Translation through Phrase Pair Variables. In M. Utiyama, & R. Wang (Eds.), MTS: Machine Translation Summit 2023: September 4-8, 2023, Macau SAR, China : Proceedings of Machine Translation Summit XIX. - Vol. 1: Research Track (pp. 12-25). Asia-Pacific Association for Machine Translation. https://aclanthology.org/2023.mtsummit-research.2 [details]
    • Liao, B., & Monz, C. (2023). Ask Language Model to Clean Your Noisy Translation Data. In H. Bouamor, J. Pino, & K. Bali (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2023: The 2023 Conference on Empirical Methods in Natural Language Processing (pp. 3215-3236). ACL. https://aclanthology.org/2023.findings-emnlp.212/ [details]
    • Liao, B., Meng, Y., & Monz, C. (2023). Parameter-Efficient Fine-Tuning without Introducing New Latency. In A. Rogers, J. Boyd-Graber, & N. Okazaki (Eds.), The 61st Conference of the Association for Computational Linguistics: Proceedings of the Conference : ACL 2023 : July 9-14, 2023 (Vol. 1, pp. 4242–4260). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.acl-long.233 [details]
    • Liao, B., Tan, S., & Monz, C. (2023). Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning. In Thirty-seventh Annual Conference on Neural Information Processing Systems OpenReview. https://openreview.net/forum?id=J8McuwS3zY [details]
    • Naszádi, K., Manggala, P., & Monz, C. (2023). Aligning Predictive Uncertainty with Clarification Questions in Grounded Dialog. In H. Bouamor, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing : Findings of the Association for Computational Linguistics: EMNLP 2023: December 6-10, 2023 (pp. 14988–14998). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-emnlp.999 [details]
    • Soleimani, A., Monz, C., & Worring, M. (2023). NonFactS: NonFactual Summary Generation for Factuality Evaluation in Document Summarization. In A. Rogers, J. Boyd-Graber, & N. Okazaki (Eds.), Findings of the Association for Computational Linguistics: ACL 2023: July 9-14, 2023 (pp. 6405-6419). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-acl.400 [details]
    • Stap, D., & Monz, C. (2023). Multilingual k-Nearest-Neighbor Machine Translation. In H. Bouamor, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 : Proceedings of the Conference : December 6-10, 2023 (pp. 9200–9208). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.571 [details]
    • Stap, D., Niculae, V., & Monz, C. (2023). Viewing Knowledge Transfer in Multilingual Machine Translation Through a Representational Lens. In H. Bouamor, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing : Findings of the Association for Computational Linguistics: EMNLP 2023: December 6-10, 2023 (pp. 14973–14987). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-emnlp.998 [details]
    • Tan, S., & Monz, C. (2023). Towards a Better Understanding of Variations in Zero-Shot Neural Machine Translation Performance. In The 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 (pp. 13553–13568). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.836
    • Wu, D., & Monz, C. (2023). Beyond Shared Vocabulary: Increasing Representational Word Similarities across Languages for Multilingual Machine Translation. In The 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 (pp. 9749–9764). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.605
    • Wu, D., Tan, S., Stap, D., Araabi, A., & Monz, C. (2023). UvA-MT’s Participation in the WMT 2023 General Translation Shared Task. In P. Koehn, B. Haddow, T. Kocmi, & C. Monz (Eds.), Eighth Conference on Machine Translation: WMT 2023 : December 6-7, 2023 (pp. 175–180). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.wmt-1.17 [details]

    2022

    • Araabi, A., Monz, C., & Niculae, V. (2022). How Effective is Byte Pair Encoding for Out-Of-Vocabulary Words in Neural Machine Translation? In K. Duh, F. Guzmán, & S. Richardson (Eds.), Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), AMTA 2022, Orlando, USA, September 12-16, 2022 (pp. 117-130). Association for Machine Translation in the Americas. https://aclanthology.org/2022.amta-research.9
    • Liao, B., Thulke, D., Hewavitharana, S., Ney, H., & Monz, C. (2022). Mask More and Mask Later: Efficient Pre-training of Masked Language Models by Disentangling the [MASK] Token. In Y. Goldberg, Z. Kozareva, & Y. Zhang (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2022: Conference on Empirical Methods in Natural Language Processing (EMNLP), Abu Dhabi, United Arab Emirates, 7-11 December 2022 (pp. 1478–1492). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2211.04898, https://doi.org/10.18653/v1/2022.findings-emnlp.106 [details]

    2021

    2020

    • Akata, Z., Balliet, D., de Rijke, M., Dignum, F., Dignum, V., Eiben, G., Fokkens, A., Grossi, D., Hindriks, K., Hoos, H., Hung, H., Jonker, C., Monz, C., Neerincx, M., Oliehoek, F., Prakken, H., Schlobach, S., van der Gaag, L., van Harmelen, F., ... Welling, M. (2020). A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer, 53(8), 18-28. https://doi.org/10.1109/MC.2020.2996587 [details]
    • Meng, C., Ren, P., Chen, Z., Monz, C., Ma, J., & de Rijke, M. (2020). RefNet: A Reference-Aware Network for Background Based Conversation. In AAAI-20, IAAI-20, EAAI-20 proceedings: Thirty-Fourth AAAI Conference on Artificial Intelligence, Thirty-Second Conference on Innovative Applications of Artificial Intelligence, The Tenth Symposium on Educational Advances in Artificial Intelligence : February 7–12th, 2020, New York Hilton Midtown, New York, New York, USA (Vol. 5, pp. 8496-8503). (Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 34). AAAI Press. https://doi.org/10.1609/aaai.v34i05.6370 [details]
    • Pei, J., Ren, P., Monz, C., & de Rijke, M. (2020). Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation. In G. De Giacomo, A. Catala, B. Dilkina, M. Milano, S. Barro, A. Bugarín, & J. Lang (Eds.), ECAI 2020: 24th European Conference on Artificial Intelligence : 29 August-8 September 2020, Santiago de Compostela, Spain, including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) : proceedings (pp. 2148-2155). ( Frontiers in Artificial Intelligence and Applications; Vol. 325). IOS Press. https://doi.org/10.3233/FAIA200339 [details]
    • Ren, P., Chen, Z., Monz, C., Ma, J., & de Rijke, M. (2020). Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation. In AAAI-20, IAAI-20, EAAI-20 proceedings: Thirty-Fourth AAAI Conference on Artificial Intelligence, Thirty-Second Conference on Innovative Applications of Artificial Intelligence, The Tenth Symposium on Educational Advances in Artificial Intelligence : February 7–12th, 2020, New York Hilton Midtown, New York, New York, USA (Vol. 5, pp. 8697-8704). (Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 34). AAAI Press. https://doi.org/10.1609/aaai.v34i05.6395 [details]
    • Soleimani, A., Monz, C., & Worring, M. (2020). BERT for Evidence Retrieval and Claim Verification. In J. M. Jose, E. Yilmaz, J. Magalhães, P. Castells, N. Ferro, M. J. Silva, & F. Martins (Eds.), Advances in Information Retrieval: 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14–17, 2020 : proceedings (Vol. II, pp. 359-366). (Lecture Notes in Computer Science; Vol. 12036). Springer. https://doi.org/10.1007/978-3-030-45442-5_45 [details]

    2019

    • Jiang, S., Ren, P., Monz, C., & de Rijke, M. (2019). Improving Neural Response Diversity with Frequency-Aware Cross-Entropy Loss. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 2879-2885). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313415 [details]

    2018

    • Fadaee, M., & Monz, C. (2018). Back-Translation Sampling by Targeting Difficult Words in Neural Machine Translation. In E. Riloff, D. Chiang, J. Hockenmaier, & J. Tsujii (Eds.), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018: Brussels, Belgium, Oct. 31-Nov. 4 (pp. 436-446). The Association for Computational Linguistics. https://doi.org/10.18653/v1/D18-1040 [details]
    • Fadaee, M., Bisazza, A., & Monz, C. (2018). Examining the Tip of the Iceberg: A Data Set for Idiom Translation. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), LREC 2018 : Eleventh International Conference on Language Resources and Evaluation: May 7-12, 2018, Miyazaki, Japan (pp. 925-929). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2018/summaries/432.html [details]
    • Tran, K., Bisazza, A., & Monz, C. (2018). The Importance of Being Recurrent for Modeling Hierarchical Structure. In E. Riloff, D. Chiang, J. Hockenmaier, & J. Tsujii (Eds.), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018: Brussels, Belgium, Oct. 31-Nov. 4 (pp. 4731–4736). The Association for Computational Linguistics. https://doi.org/10.18653/v1/D18-1503 [details]
    • van der Wees, M., Bisazza, A., & Monz, C. (2018). Evaluation of Machine Translation Performance Across Multiple Genres and Languages. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), LREC 2018 : Eleventh International Conference on Language Resources and Evaluation: May 7-12, 2018, Miyazaki, Japan (pp. 3822-3827). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2018/summaries/853.html [details]

    2017

    • Fadaee, M., Bisazza, A., & Monz, C. (2017). Data Augmentation for Low-Resource Neural Machine Translation. In R. Barzilay, & M-Y. Kan (Eds.), The 55th Annual Meeting of the Association for Computational Linguistics: proceedings of the Conference : July 30-August 4, 2017, Vancouver, Canada (Vol. 2, pp. 567-573). Association for Computational Linguistics. https://doi.org/10.18653/v1/P17-2090 [details]
    • Fadaee, M., Bisazza, A., & Monz, C. (2017). Learning Topic-Sensitive Word Representations. In R. Barzilay, & M-Y. Kan (Eds.), The 55th Annual Meeting of the Association for Computational Linguistics: proceedings of the Conference : July 30-August 4, 2017, Vancouver, Canada (Vol. 2, pp. 441-447). Association for Computational Linguistics. https://doi.org/10.18653/v1/P17-2070 [details]
    • Ghader, H., & Monz, C. (2017). What does Attention in Neural Machine Translation Pay Attention to? In G. Kondrak, & T. Watanabe (Eds.), The Eight International Joint Conference on Natural Language Processing: proceedings of the Conference : November 27-December 1, 2017, Taipei, Taiwan (Vol. 1, pp. 30-39). Asian Federation of Natural Language Processing. http://www.aclweb.org/anthology/I17-1004 [details]
    • van der Wees, M., Bisazza, A., & Monz, C. (2017). Dynamic Data Selection for Neural Machine Translation. In M. Palmer, R. Hwa, & S. Riedel (Eds.), The Conference on Empirical Methods in Natural Language Processing: proceedings of the conference : EMNLP 2017 : September 9-11, 2017, Copenhagen, Denmark (pp. 1400-1410). Association for Computational Linguistics. https://doi.org/10.18653/v1/D17-1147 [details]

    2016

    • Bellegarda, J. R., & Monz, C. (2016). State of the Art in Statistical Methods for Language and Speech Processing. Computer Speech and Language, 35, 163-184. Advance online publication. https://doi.org/10.1016/j.csl.2015.07.001 [details]
    • Bojar, O., Chatterjee, R., Federmann, C., Graham, Y., Haddow, B., Huck, M., Jimeno Yepes, A., Koehn, P., Logacheva, V., Monz, C., Negri, M., Névéol, A., Neves, M., Popel, M., Post, M., Rubino, R., Scarton, C., Specia, L., Turchi, M., ... Zampieri, M. (2016). Findings of the 2016 Conference on Machine Translation (WMT16). In Proceedings of the First Conference on Machine Translation: Berlin, Germany, August 11-12, 2016 (Vol. 2, pp. 131-198). Association for Computational Linguistics. https://doi.org/10.18653/v1/W16-2301 [details]
    • Dakwale, P., & Monz, C. (2016). Improving Statistical Machine Translation Performance by Oracle-BLEU Model Re-estimation. In K. Erk, & N. A. Smith (Eds.), The 54th Annual Meeting of the Association for Computational Linguistics : ACL 2016: proceedings of the conference : August 7-12, 2016, Berlin Germany (Vol. 2, pp. 38-44). Association for Computational Linguistics. https://doi.org/10.18653/v1/P16-2007 [details]
    • Garmash, E., & Monz, C. (2016). Ensemble Learning for Multi-Source Neural Machine Translation. In Y. Matsumoto, & R. Prasad (Eds.), Proceedings of COLING 2016: technical papers: the 26th International Conference on Computational Linguistics : Osaka, Japan, December 11-17 2016 (pp. 1409-1418). The COLING 2016 Organizing Committee. https://www.aclweb.org/anthology/C16-1133 [details]
    • Ghader, H., & Monz, C. (2016). Which Words Matter in Defining Phrase Reorderings in Statistical Machine Translation? In Proceedings of the Meeting of the Association for Machine Translation in the Americas (AMTA-2016) (pp. 149-162). Association for Machine Translation in the Americas. https://amtaweb.org/wp-content/uploads/2016/10/AMTA2016_Research_Proceedings_v7.pdf#page=155
    • Tran, K., Bisazza, A., & Monz, C. (2016). Recurrent Memory Networks for Language Modeling. In K. Knight, A. Nenkova, & O. Rambow (Eds.), NAACL HLT 2016 : The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Proceedings of the Conference : June 12-17, 2016, San Diego, California, USA (pp. 321-331). The Association for Computational Linguistics. https://doi.org/10.18653/v1/N16-1036 [details]
    • van der Wees, M., Bisazza, A., & Monz, C. (2016). A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation. In WNUT 2016 : the 2nd Workshop on Noisy User-generated Text: proceedings of the Workshop : December 11, 2016, Osaka, Japan (pp. 43-50). The COLING 2016 Organizing Committee. http://aclweb.org/anthology/W16-3908 [details]
    • van der Wees, M., Bisazza, A., & Monz, C. (2016). Measuring the Effect of Conversational Aspects on Machine Translation Quality. In Y. Matsumoto, & R. Prasad (Eds.), Proceedings of COLING 2016: technical papers: the 26th International Conference on Computational Linguistics : Osaka, Japan, December 11-17 2016 (pp. 2571-2581). The COLING 2016 Organizing Committee. http://aclweb.org/anthology/C16-1242 [details]

    2015

    • Bojar, O., Chatterjee, R., Federmann, C., Haddow, B., Huck, M., Hokamp, C., Koehn, P., Logacheva, V., Monz, C., Negri, M., Post, M., Scarton, C., Specia, L., & Turchi, M. (2015). Findings of the 2015 Workshop on Statistical Machine Translation. In EMNLP 2015 : Tenth Workshop on Statistical Machine Translation: proceedings of the workshop : 17-18 September 2015, Lisbon, Portugal (pp. 1-46). The Association for Computational Linguistics. https://doi.org/10.18653/v1/W15-3001 [details]
    • Garmash, E., & Monz, C. (2015). Bilingual Structured Language Models for Statistical Machine Translation. In L. Márquez, C. Callison-Burch, & J. Su (Eds.), EMNLP 2015 Lisbon : conference proceedings: September 17-21 : Conference on Empirical Methods in Natural Language Processing (pp. 2398-2408). The Association for Computational Linguistics. https://aclweb.org/anthology/D/D15/D15-1287.pdf [details]
    • Tran, K., Bisazza, A., & Monz, C. (2015). A Distributed Inflection Model for Translating into Morphologically Rich Languages. In Y. Al-Onaizan, & W. Lewis (Eds.), Proceedings of MT Summit XV. - Vol. 1: MT Researchers' Track: MT Summit XV : October 30-November 3, 2015, Miami, FL, USA (pp. 145-159). Association for Machine Translation in the Americas. http://www.mt-archive.info/15/MTS-2015-Tran.pdf [details]
    • van der Wees, M., Bisazza, A., & Monz, C. (2015). Five Shades of Noise: Analyzing Machine Translation Errors in User-Generated Text. In W. Xu, B. Han, & A. Ritter (Eds.), ACL-IJCNLP 2015 : ACL 2015 Workshop on Noisy User-generated Text: proceedings of the workshop : July 31, 2015, Beijing, China (pp. 28-37). The Association for Computational Linguistics. http://www.aclweb.org/anthology/W/W15/W15-4304.pdf [details]
    • van der Wees, M., Bisazza, A., & Monz, C. (2015). Translation Model Adaptation Using Genre-Revealing Text Features. In B. Webber, M. Carpuat, A. Popescu-Belis, & C. Hardmeier (Eds.), DiscoMT 2015 : Discourse in Machine Translation: proceedings of the workshop : 17 September 2015, Lisbon, Portugal (pp. 132-141). The Association for Computational Linguistics. http://www.aclweb.org/anthology/W/W15/W15-2518.pdf [details]
    • van der Wees, M., Bisazza, A., Weerkamp, W., & Monz, C. (2015). What's in a Domain? Analyzing Genre and Topic Differences in Statistical Machine Translation. In C. Zong, & M. Strube (Eds.), ACL-IJCNLP 2015: The 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing : proceedings of the conference : ACL 2015, July 26-31, Beijing, China (Vol. 2, pp. 560-566). Association for Computational Linguistics. http://www.aclweb.org/anthology/P/P15/P15-2092.pdf [details]

    2014

    • Bisazza, A., & Monz, C. (2014). Class-Based Language Modeling for Translating into Morphologically Rich Languages. In J. Tsujii, & J. Hajic (Eds.), COLING 2014: the 25th International Conference on Computational Linguistics: proceedings of COLING 2014 : technical papers: August 23-29, 2014, Dublin, Ireland (pp. 1918-1927). Association for Computational Linguistics. http://www.aclweb.org/anthology/C14-1181 [details]
    • Bojar, O., Buck, C., Federmann, C., Haddow, B., Koehn, P., Leveling, J., Monz, C., Pecina, P., Post, M., Saint-Amand, H., Soricut, R., Specia, L., & Tamchyna, A. (2014). Findings of the 2014 Workshop on Statistical Machine Translation. In O. Bojar, C. Buck, C. Federmann, B. Haddow, P. Koehn, C. Monz, M. Post, & L. Specia (Eds.), ACL 2014: Ninth Workshop on Statistical Machine Translation: proceedings of the workshop: June 26-27, 2014, Baltimore, Maryland, USA (pp. 12-58). Association for Computational Linguistics. http://www.aclweb.org/anthology/W/W14/W14-3302.pdf [details]
    • Garmash, E., & Monz, C. (2014). Dependency-Based Bilingual Language Models for Reordering in Statistical Machine Translation. In A. Moschitti, B. Pang, & W. Daelemans (Eds.), EMNLP 2014: the 2014 Conference on Empirical Methods in Natural Language Processing: proceedings of the conference: October 25-29, 2014, Doha, Qatar (pp. 1689-1700). Association for Computational Linguistics. http://www.aclweb.org/anthology/D14-1176 [details]
    • Martzoukos, S., Costa Florêncio, C., & Monz, C. (2014). Maximizing Component Quality in Bilingual Word-Aligned Segmentations. In S. Wintner, S. Goldwater, & S. Riezler (Eds.), EACL 2014: 14th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference: April 26-30, 2014, Gothenburg, Sweden (pp. 30-38). Association for Computational Linguistics. http://www.aclweb.org/anthology/E/E14/E14-1004.pdf [details]
    • Tran, K., Bisazza, A., & Monz, C. (2014). Word Translation Prediction for Morphologically Rich Languages with Bilingual Neural Networks. In A. Moschitti, B. Pang, & W. Daelemans (Eds.), EMNLP 2014: the 2014 Conference on Empirical Methods in Natural Language Processing: proceedings of the conference: October 25-29, 2014, Doha, Qatar (pp. 1676-1688). Association for Computational Linguistics. http://www.aclweb.org/anthology/D/D14/D14-1175.pdf [details]

    2013

    • Martzoukos, S., Costa Florêncio, C., & Monz, C. (2013). Investigating Connectivity and Consistency Criteria for Phrase Pair Extraction in Statistical Machine Translation. In A. Kornai, & M. Kuhlmann (Eds.), MoL 13: the 13th Meeting on the Mathematics of Language: proceedings: August 9, 2013, Sofia, Bulgaria (pp. 93-101). Association for Computational Linguistics. http://aclweb.org/anthology/W/W13/W13-3010.pdf [details]

    2012

    • Bronner, A., & Monz, C. (2012). User edits classification using document revision histories. In W. Daelemans (Ed.), EACL 2012: 13th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference : April 23-27 2012, Avignon France (pp. 356-366). Association for Computational Linguistics. http://www.aclweb.org/anthology/E/E12/E12-1036.pdf [details]
    • Martzoukos, S., & Monz, C. (2012). Power-Law Distributions for Paraphrases Extracted from Bilingual Corpora. In W. Daelemans (Ed.), EACL 2012: 13th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference : April 23-27 2012, Avignon France (pp. 2-11). Association for Computational Linguistics. http://www.aclweb.org/anthology/E/E12/E12-1002.pdf [details]
    • Nikoulina, V., Kovachev, B., Lagos, N., & Monz, C. (2012). Adaptation of Statistical Machine Translation Model for Cross-Lingual Information Retrieval in a Service Context. In W. Daelemans (Ed.), EACL 2012: 13th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference : April 23-27 2012, Avignon France (pp. 109-119). Association for Computational Linguistics. http://www.aclweb.org/anthology/E/E12/E12-1002.pdf [details]

    2011

    2010

    2009

    • Callison-Burch, C., Koehn, P., Monz, C., & Schroeder, J. (2009). Findings of the 2009 Workshop on Statistical Machine Translation. In C. Callison-Burch, P. Koehn, C. Monz, & J. Schroeder (Eds.), Proceedings of the Fourth Workshop on Statistical Machine Translation, Athens, Greece (pp. 1-28). Association for Computational Linguistics. http://portal.acm.org/citation.cfm?id=1626431.1626433 [details]
    • Carter, S., & Monz, C. (2009). Parsing statistical machine translation output. In Z. Vetulani (Ed.), Human language technologies as a challenge for computer science and linguistics: 4th Language & Technology Conference, November, 6-8, 2009, Poznań, Poland: proceedings (pp. 270-274). Wydawnictwo Poznańskie. http://www.scarter.org/ltc2009-CameraReady.pdf [details]
    • Habash, N., Dorr, B., & Monz, C. (2009). Symbolic-to-statistical hybridization: extending generation-heavy machine translation. Machine Translation, 23(1), 23-63. https://doi.org/10.1007/s10590-009-9056-7 [details]
    • Kastner, I., & Monz, C. (2009). Automatic single-document key fact extraction from newswire articles. In A. Lascarides, C. Gardent, & J. Nivre (Eds.), Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: EACL 2009: 30 March-3 April 2009, Megaron Athens International Conference Centre, Athens, Greece (pp. 415-423). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1609067.1609113 [details]
    • Monz, C., & Weerkamp, W. (2009). A comparison of retrieval-based hierarchical clustering approaches to person name disambiguation. In M. Sanderson, C. Zhai, J. Zobel, J. Allan, & J. A. Aslam (Eds.), 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2009), Boston, MA, USA (pp. 650-651). ACM. http://doi.acm.org/10.1145/1571941.1572060 [details]
    • Yahyaei, S., & Monz, C. (2009). Decoding by dynamic chunking for statistical machine translation. In L. Gerber, P. Isabelle, R. Kuhn, N. Bemish, M. Dillinger, & M-J. Goulet (Eds.), MT Summit XII: Proceedings of the twelfth Machine Translation Summit, Ottawa, Ontario, Canada (pp. 160-167). International Association for Machine Translation (IAMT). http://www.mt-archive.info/MTS-2009-Yahyaei.pdf [details]

    2008

    2021

    • Soleimani, A., Monz, C., & Worring, M. (2021). NLQuAD: A Non-Factoid Long Question Answering Data Set. In P. Merlo, J. Tiedemann, & R. Tsarfaty (Eds.), The 16th Conference of the European Chapter of the Association for Computational Linguistics: EACL 2021 : proceedings of the conference : April 19-23, 2021 (pp. 1245-1255). Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.eacl-main.106 [details]

    2020

    • Araabi, A., & Monz, C. (2020). Optimizing Transformer for Low-Resource Neural Machine Translation. In D. Scott, N. Bel, & C. Zong (Eds.), The 28th International Conference on Computational Linguistics: COLING 2020 : Proceedings of the Conference : December 8-13, 2020, Barcelona, Spain (Online) (pp. 3429-3435). International Committee on Computational Linguistics. https://doi.org/10.18653/v1/2020.coling-main.304 [details]
    • Jiang, S., Wolf, T., Monz, C., & de Rijke, M. (2020). TLDR: Token Loss Dynamic Reweighting for Reducing Repetitive Utterance. (v2 ed.) ArXiv. https://doi.org/10.48550/arXiv.2003.11963 [details]

    2011

    2009

    2017

    • Dakwale, P., & Monz, C. (2017). Convolutional over Recurrent Encoder for Neural Machine Translation. Paper presented at The 20th Annual Conference of the European Association for Machine Translation (EAMT), Prague, Czech Republic.
    • Dakwale, P., & Monz, C. (2017). Fine-tuning for neural machine translation with limited degradation across in-and out-of-domain data. Paper presented at Machine translation summit XVI, Nagoya, Japan.

    2016

    • Heuer, H., Monz, C., & Smeulders, A. W. M. (2016). Generating Captions without Looking Beyond Objects. Paper presented at ECCV2016 2nd Workshop on Storytelling with Images and Videos, Amsterdam, Netherlands. https://arxiv.org/abs/1610.03708

    2017

    • van der Wees, M. E. (2017). What’s in a domain? Towards fine-grained adaptation for machine translation. [Thesis, fully internal, Universiteit van Amsterdam]. [details]

    2019

    2023

    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
  • Ancillary activities
    • No ancillary activities