Search
photo of Pranava Madhyastha

Dr Pranava Madhyastha

Lecturer in Computer Science

School of Science & Technology Department of Computer Science

Contact details

Address

Dr Pranava Madhyastha City, University of London
Northampton Square
London EC1V 0HB
United Kingdom

Personal links

About

Overview

Dr Pranava Madhyastha is a Lecturer in Computer Science where he studies multimodal machine learning models for natural language understanding and generation. He is especially interested in applying computational models to scientific questions in syntax, semantics, and broadly in language communication.

Qualifications

  • PhD, Universitat Politècnica de Catalunya, Spain, Feb 2012 – Jul 2017

Employment

  • Honorary Research Fellow, Imperial College London, Oct 2021 – present
  • Lecturer in Computer Science, City, University of London, Jul 2021 – present
  • Research Fellow, Imperial College London, Oct 2018 – Jun 2021
  • Research Fellow in Machine Learning, University of Sheffield, Oct 2016 – Sep 2018

Publications

Publications by category

Conference papers and proceedings (36)

  • Whitehouse, C., Weyde, T., Madhyastha, P. and Komninos, N. (2022). Evaluation of Fake News Detection with Knowledge-Enhanced Language Models. Proceedings of the Sixteenth International AAAI Conference on Web and Social Media, ICWSM 2022 6-9 June, Atlanta, Georgia, USA.
  • El-Naggar, N., Madhyastha, P. and Weyde, T. (2022). Experiments in Learning Dyck-1 Languages with Recurrent Neural Networks.
  • Madhyastha, P. (2022). Towards Integration of Embodiment Features for Prosodic Prominence Prediction from Text. ICMI '22: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION.
  • Al-Negheimish, H., Madhyastha, P. and Russo, A. (2021). Numerical reasoning in machine reading comprehension tasks: are we there yet?
  • Ive, J., Li, A.M., Miao, Y., Caglayan, O., Madhyastha, P. and Specia, L. (2021). Exploiting multimodal reinforcement learning for simultaneous machine translation.
  • Caglayan, O., Kuyu, M., Amac, M.S., Madhyastha, P., Erdem, E., Erdem, A. … Specia, L. (2021). Cross-lingual visual pre-training for multimodal machine translation.
  • Al-Negheimish, H., Madhyastha, P. and Russo, A. (2021). Discrete reasoning templates for natural language understanding.
  • López, J.A.D. and Madhyastha, P. (2021). A focused analysis of twitter-based disinformation from foreign influence operations.
  • Mitzalis, F., Caglayan, O., Madhyastha, P. and Specia, L. (2021). BERTGEN: Multi-task generation through BERT.
  • Scarton, C., Madhyastha, P. and Specia, L. (2020). Deciding when, how and for whom to simplify.
  • Caglayan, O., Ive, J., Haralampieva, V., Madhyastha, P., Barrault, L. and Specia, L. (2020). Simultaneous machine translation with visual context.
  • Ive, J., Madhyastha, P. and Specia, L. (2019). Deep Copycat Networks for Text-to-Text Generation. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) November.
  • Madhyastha, P. and Jain, R. (2019). On Model Stability as a Function of Random Seed. Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL) November.
  • Chow, J., Specia, L. and Madhyastha, P. (2019). WMDO: Fluency-based Word Mover’s Distance for Machine Translation Evaluation. Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) August.
  • Ive, J., Madhyastha, P. and Specia, L. (2019). Distilling Translations with Visual Awareness. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics July.
  • Madhyastha, P., Wang, J. and Specia, L. (2019). VIFIDEL: Evaluating the Visual Fidelity of Image Descriptions. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics July.
  • Caglayan, O., Madhyastha, P., Specia, L. and Barrault, L. (2019). Probing the Need for Visual Context in Multimodal Machine Translation. Proceedings of the 2019 Conference of the North June.
  • Holzenberger, N., Palaskar, S., Madhyastha, P., Metze, F. and Arora, R. (2019). Learning from Multiview Correlations in Open-domain Videos. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 12-17 May.
  • Madhyastha, P., Wang, J. and Specia, L. (2019). End-to-end image captioning exploits multimodal distributional similarity.
  • Chow, J., Madhyastha, P. and Specia, L. (2019). WMDO: Fluency-based word Mover's distance for machine translation evaluation.
  • Madhyastha, P.S., Wang, J. and Specia, L. (2018). End-to-end Image Captioning Exploits Distributional Similarity in Multimodal Space. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP November.
  • Lala, C., Madhyastha, P.S., Scarton, C. and Specia, L. (2018). Sheffield Submissions for WMT18 Multimodal Translation Shared Task. Proceedings of the Third Conference on Machine Translation: Shared Task Papers October.
  • Madhyastha, P.S., Wang, J. and Specia, L. (2018). Defoiling Foiled Image Captions. Proceedings of the 2018 Conference of the North American Chapter of
    the Association for Computational Linguistics: Human Language
    Technologies, Volume 2 (Short Papers)     June.
  • Wang, J., Madhyastha, P.S. and Specia, L. (2018). Object Counts! Bringing Explicit Detections Back into Image Captioning. Proceedings of the 2018 Conference of the North American Chapter of
    the Association for Computational Linguistics: Human Language
    Technologies, Volume 1 (Long Papers)     June.
  • Lala, C., Madhyastha, P., Scarton, C. and Specia, L. (2018). Sheffield Submissions for WMT18 Multimodal Translation Shared Task.
  • Deena, S., Ng, R.W.M., Madhyastha, P., Specia, L. and Hain, T. (2017). Exploring the use of acoustic embeddings in neural machine translation. 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) 16-20 December.
  • Madhyastha, P.S., Wang, J. and Specia, L. (2017). Sheffield MultiMT: Using Object Posterior Predictions for Multimodal
    Machine Translation.     Proceedings of the Second Conference on Machine Translation September.
  • Madhyastha, P.S. and España-Bonet, C. (2017). Learning Bilingual Projections of Embeddings for Vocabulary
    Expansion in Machine Translation.     Proceedings of the 2nd Workshop on Representation Learning for NLP August.
  • Madhyastha, P.S., Carreras, X. and Quattoni, A. (2017). Prepositional phrase attachment over word embedding products.
  • Madhyastha, P.S., Bansal, M., Gimpel, K. and Livescu, K. (2016). Mapping Unseen Words to Task-Trained Embedding Spaces. Proceedings of the 1st Workshop on Representation Learning for NLP August.
  • Costa-jussà, M.R., España-Bonet, C., Madhyastha, P., Escolano, C. and Fonollosa, J.A.R. (2016). The TALP–UPC Spanish–English WMT Biomedical Task: Bilingual
    Embeddings and Char-based Neural Language Model Rescoring in a
    Phrase-based System.     Proceedings of the First Conference on Machine Translation: Volume 2,
    Shared Task Papers     August.
  • Quattoni, A., Ramisa, A., Madhyastha, P.S., Simo-Serra, E. and Moreno-Noguer, F. (2016). Structured Prediction with Output Embeddings for Semantic Image Annotation. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies June.
  • Ellebracht, L.D., Ramisa, A., Madhyastha, P.S., Cordero-Rama, J., Moreno-Noguer, F. and Quattoni, A. (2015). Semantic Tuples for Evaluation of Image to Sentence Generation. Proceedings of the Fourth Workshop on Vision and Language September.
  • Madhyastha, P.S., Carreras, X. and Quattoni, A. (2015). Tailoring word embeddings for bilexical predictions: An experimental comparison.
  • Madhyastha, P.S., Carreras, X. and Quattoni, A. (2014). Learning task-specific bilexical embeddings.
  • Deena, S., Ng, R.W.M., Madhyastha, P., Specia, L. and Hain, T. Semi-Supervised Adaptation of RNNLMs by Fine-Tuning with Domain-Specific Auxiliary Features. Interspeech 2017.

Journal articles (5)