WG2 focuses on efficient ML machinery behind state-of-the-art Language Generation (LG) models, since much of the improvements we observe across different LG tasks nowadays are due to the application of varied deep neural network architectures. This involves, among others:
- multi-task learning
- transfer learning
- representation learning
- structured prediction
- generative models
Moreover, WG2 investigates integration strategies for multi-modal data, which is of critical importance for Multi3Generation.
This working group will be working on:
- a repository of open source software for processing language and visual content, inc. a directory of sources of materials or components
- a survey on efficient use of ML for LG
- the organization of training schools
If you would like to join this working group, please contact the WG Leader and coleader: Aykut Erdem (aykut-at-cs.hacettepe.edu.tr) and Elena Lloret (elloret-at-dlsi.ua.es)
Publications and preprints
- Ales Zamuda and Elena Lloret. Optimizing Data Driven Models for Summarization as Parallel Tasks, Journal of Computational Science, Vol. 42, April 2020.
- Begum Citamak, Ozan Caglayan, Menekse Kuyu, Erkut Erdem, Aykut Erdem, Pranava Madhyastha, Lucia Specia. MSVD-Turkish: A Comprehensive Multimodal Video Dataset for Integrated Vision and Language Research in Turkish, Machine Translation, Vol. 35, 265-288.
- Emre Boran, Aykut Erdem, Nazli Ikizler-Cinbis, Erkut Erdem, Pranava Madhyastha, Lucia Specia. Leveraging auxiliary image descriptions for dense video captioning, Pattern Recognition Letters, Vol. 146, June 2021.
- Erkut Erdem, Menekse Kuyu, Semih Yagcioglu, Anette Frank, Letitia Parcalabescu, Andrii Babii, Olek- sii Turuta, Aykut Erdem, Iacer Calixto, Barbara Plank, Elena Lloret, Elena-Simona Apostol, Ciprian- Octavian Truica ̆, Branislava Šandrih, Sanda Martinčić-Ipšić, Gábor Berend, Albert Gatt, Grazina Korvel, “Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning”, Journal of Artificial Intelligence Research, Vol. 73, pp. 1131-1207, April 2022.
- César González-Mora, Cristina Barros, Irene Garrigós, José Jacobo Zubcoff, Elena Lloret, Jose-Norberto Mazón: Improving open data web API documentation through interactivity and natural language generation. Computer Standards & Interfaces 83: 103657 (2023).
- Robiert Sepúlveda-Torres, Marta Esther Vicente, Estela Saquete, Elena Lloret, Manuel Palomar: HeadlineStanceChecker: Exploiting summarization to detect headline disinformation. Journal of Web Semantics 71: 100660 (2021).
- M. Sercan Amac , Semih Yagcioglu , Aykut Erdem, and Erkut Erdem. “Procedural Reasoning Networks for Understanding Multimodal Procedures“, In 23rd Conference on Computational Natural Language Learning (CoNLL).
- J. Phang, I. Calixto, PM. Htut, Y. Pruksachatkun, H. Liu, C. Vania, K. Kann, SR. Bowman (2020). English intermediate-task training improves zero-shot cross-lingual transfer too. In AACL 2020.
- V. Milewski , MF. Moens and I. Calixto (2020). Are scene graphs good enough to improve image captioning? In: AACL 2020.
- Ozan Caglayan, Menekse Kuyu, Mustafa Sercan Amac, Pranava Madhyastha, Erkut Erdem, Aykut Erdem and Lucia Specia. Cross-lingual Visual Pre-training for Multimodal Machine Translation, Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021), Short Papers, 2021.
- Rob van der Goot, Ahmet Üstün, Alan Ramponi, Ibrahim Sharaf and Barbara Plank. Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP. In EACL 2021. Received EACL 2021 oustanding paper award (demo track)
- Ilker Kesen, Ozan Arkan Can, Erkut Erdem, Aykut Erdem, Deniz Yuret, “Modulating Bottom-Up and Top-Down Visual Processing via Language-Conditional Filters”, 5th Multimodal Learning and Applications Workshop (MULA 2022) – in conjunction with CVPR 2022 (Best Paper Award), New Orleans, USA, June 2022.
- Anabela Barreiro, José GC de Souza, Albert Gatt, Mehul Bhatt, Elena Lloret, Aykut Erdem, Dimitra Gkatzia, Helena Moniz, Irene Russo, Fabio Kepler, Iacer Calixto, Marcin Paprzycki, François Portet, Isabelle Augenstein, Mirela Alhasani, “Multi3Generation: Multitask, Multilingual, Multimodal Language Generation”, 23rd Annual Conference of the European Association for Machine Translation (EAMT 2022), Ghent, Belgium, June 2022.
- Tayfun Ates, Muhammed Samil Atesoglu, Cagatay Yigit, Ilker Kesen, Mert Kobas, Erkut Erdem, Aykut Erdem, Tilbe Goksun, Deniz Yuret, “CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions“, Findings of the Association for Computational Linguistics (ACL 2022), May 2022.
- Parcalabescu, L., Cafagna, M., Muradjan, L., Frank, A., Calixto, I. and Gatt, A., 2022, May. VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 8253-8280).
- Patrick Fernandes, António Farinhas, Ricardo Rei, José G. C. de Souza, Perez Ogayo, Graham Neubig, Andre Martins. Quality-Aware Decoding for Neural Machine Translation Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL). July 2022.
- Ricardo Rei, Ana C Farinha, José G.C. de Souza, Pedro G. Ramos, André F.T. Martins, Luisa Coheur, Alon Lavie. Searching for COMETINHO: The Little Metric That Could. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 61–70, Ghent, Belgium. European Association for Machine Translation.
- Ilker Kesen, Aykut Erdem, Erkut Erdem, Iacer Calixto. “Detecting Euphemisms with Literal Descriptions and Visual Imagery”, The Third Workshop on Figurative Language Processing (FigLang 2022), in conjunction with EMNLP 2022.
- D. Dashenkov, K. Smelyakov and O. Turuta, “Methods of Multilanguage Question Answering,” 2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T), 2021, pp. 251-255.
- Selim Fekih, Nicolo’ Tamagnone, Benjamin Minixhofer, Ranjan Shrestha, Ximena Contla, Ewan Oglethorpe and Navid Rekabsaz, “HumSet: Dataset of Multilingual Information Extraction and Classification for Humanitarian Crises Response” In Findings of the 2022 Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP), December 2022.
- Benjamin Minixhofer, Fabian Paischer, Navid Rekabsaz, “WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models” In proceeding of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), July 2022.
|Dataset name and brief description, including purpose||Authors/creators||Link|
|MSVD-Turkish: The first large scale video captioning dataset for Turkish languages, obtained by carefully translating the English descriptions of the videos in the MSVD (Microsoft Research Video Description Corpus) dataset into Turkish.||Begum Citamak, Ozan Caglayan, Menekse Kuyu, Erkut Erdem, Aykut Erdem, Pranava Madhyastha, and Lucia Specia.||MSVD-Turkish|
|Name and/or brief description||Authors/creators||Link|
|Procedural Reasoning Networks||Amac, M. Sercan, Yagcioglu, Semih, Erdem, Aykut, and Erdem, Erkut||https://github.com/hucvl/prn|
Open source repository
Add anything here that doesn’t clearly fall under the other headings.