A Latent Variable Model of Synchronous Syntactic-Semantic Parsing for Multiple Languages. - Andrea Gesmundo; James Henderson 001; Paola Merlo; Ivan Titov 001 (CoNLL Shared Task, 2009)

Faster cube pruning. - Andrea Gesmundo; James Henderson 001 (IWSLT, 2010)

Heuristic Search for Non-Bottom-Up Tree Structure Prediction. - Andrea Gesmundo; James Henderson 001 (EMNLP, 2011)

Classification de séquences bidirectionnelles pour des tâches d'étiquetage par apprentissage guidé (Bidirectional Sequence Classification for Tagging Tasks with Guided Learning). - Andrea Gesmundo (TALN (Articles courts), 2011)

Lemmatisation as a Tagging Task. - Andrea Gesmundo; Tanja Samardzic (ACL (2), 2012)

Heuristic Cube Pruning in Linear Time. - Andrea Gesmundo; Giorgio Satta; James Henderson 001 (ACL (2), 2012)

HadoopPerceptron: a Toolkit for Distributed Perceptron Training and Prediction with MapReduce. - Andrea Gesmundo; Nadi Tomeh (EACL, 2012)

Lemmatising Serbian as Category Tagging with Bidirectional Sequence Classification. - Andrea Gesmundo; Tanja Samardzic (LREC, 2012)

Undirected Machine Translation with Discriminative Reinforcement Learning. - Andrea Gesmundo; James Henderson 001 (EACL, 2014)

Projecting the Knowledge Graph to Syntactic Parsing. - Andrea Gesmundo; Keith B. Hall (EACL, 2014)

Algorithms and frameworks for Tree-based Machine Translation and tree structures prediction. - Andrea Gesmundo (2014)

Transfer Learning to Learn with Multitask Neural Model Search. - Catherine Wong; Andrea Gesmundo (CoRR, 2017)

Ask the Right Questions: Active Question Reformulation with Reinforcement Learning. - Christian Buck; Jannis Bulian; Massimiliano Ciaramita; Wojciech Gajewski; Andrea Gesmundo; Neil Houlsby; Wei Wang 236 (ICLR, 2018)

Transfer Learning with Neural AutoML. - Catherine Wong; Neil Houlsby; Yifeng Lu; Andrea Gesmundo (NeurIPS, 2018)

Analyzing Language Learned by an Active Question Answering Agent. - Christian Buck; Jannis Bulian; Massimiliano Ciaramita; Wojciech Gajewski; Andrea Gesmundo; Neil Houlsby; Wei Wang 236 (CoRR, 2018)

Transfer Automatic Machine Learning. - Catherine Wong; Neil Houlsby; Yifeng Lu; Andrea Gesmundo (CoRR, 2018)

Evolutionary-Neural Hybrid Agents for Architecture Search. - Krzysztof Maziarz; Andrey Khorlin; Quentin de Laroussilhe; Andrea Gesmundo (CoRR, 2018)

Neural Architecture Search Over a Graph Search Space. - Quentin de Laroussilhe; Stanislaw Jastrzebski; Neil Houlsby; Andrea Gesmundo (CoRR, 2018)

Parameter-Efficient Transfer Learning for NLP. - Neil Houlsby; Andrei Giurgiu; Stanislaw Jastrzebski; Bruna Morrone; Quentin de Laroussilhe; Andrea Gesmundo; Mona Attariyan; Sylvain Gelly (ICML, 2019)

Fast Task-Aware Architecture Inference. - Efi Kokiopoulou; Anja Hauth; Luciano Sbaiz; Andrea Gesmundo; Gábor Bartók; Jesse Berent (CoRR, 2019)

Transfer NAS: Knowledge Transfer between Search Spaces with Transformer Agents. - Zalán Borsos; Andrey Khorlin; Andrea Gesmundo (CoRR, 2019)

Gumbel-Matrix Routing for Flexible Multi-task Learning. - Krzysztof Maziarz; Efi Kokiopoulou; Andrea Gesmundo; Luciano Sbaiz; Gábor Bartók; Jesse Berent (CoRR, 2019)

Ranking architectures using meta-learning. - Alina Dubatovka; Efi Kokiopoulou; Luciano Sbaiz; Andrea Gesmundo; Gábor Bartók; Jesse Berent (CoRR, 2019)

Machine Translation of Labeled Discourse Connectives. - Thomas Meyer 003; Andrei Popescu-Belis; Najeh Hajlaoui; Andrea Gesmundo (AMTA, 2020)

Task-Aware Performance Prediction for Efficient Architecture Search. - Efi Kokiopoulou; Anja Hauth; Luciano Sbaiz; Andrea Gesmundo; Gábor Bartók; Jesse Berent (ECAI, 2020)

Temporal Coding in Spiking Neural Networks with Alpha Synaptic Function. - Iulia M. Comsa; Thomas Fischbacher; Krzysztof Potempa; Andrea Gesmundo; Luca Versari; Jyrki Alakuijala (ICASSP, 2020)

Routing Networks with Co-training for Continual Learning. - Mark Collier; Efi Kokiopoulou; Andrea Gesmundo; Jesse Berent (CoRR, 2020)

Scaling Up Models and Data with t5x and seqio. - Adam Roberts; Hyung Won Chung; Anselm Levskaya; Gaurav Mishra; James Bradbury; Daniel Andor; Sharan Narang; Brian Lester; Colin Gaffney; Afroz Mohiuddin; Curtis Hawthorne; Aitor Lewkowycz; et al. (CoRR, 2022)

muNet: Evolving Pretrained Deep Neural Networks into Scalable Auto-tuning Multitask Systems. - Andrea Gesmundo; Jeff Dean (CoRR, 2022)

An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems. - Andrea Gesmundo; Jeff Dean (CoRR, 2022)

A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems. - Andrea Gesmundo (CoRR, 2022)

A Multi-Agent Framework for the Asynchronous and Collaborative Extension of Multitask ML Systems. - Andrea Gesmundo (CoRR, 2022)

Temporal Coding in Spiking Neural Networks With Alpha Synaptic Function: Learning With Backpropagation. - Iulia-Maria Comsa; Krzysztof Potempa; Luca Versari; Thomas Fischbacher; Andrea Gesmundo; Jyrki Alakuijala (IEEE Trans. Neural Networks Learn. Syst., 2022)

Multipath agents for modular multitask ML systems. - Andrea Gesmundo (CoRR, 2023)

Composable Function-preserving Expansions for Transformer Architectures. - Andrea Gesmundo; Kaitlin Maile (CoRR, 2023)

Scaling Up Models and Data with t5x and seqio. - Adam Roberts; Hyung Won Chung; Gaurav Mishra; Anselm Levskaya; James Bradbury; Daniel Andor; Sharan Narang; Brian Lester; Colin Gaffney; Afroz Mohiuddin; Curtis Hawthorne; Aitor Lewkowycz; et al. (J. Mach. Learn. Res., 2023)