| A critique of word similarity as a method for evaluating distributional semantic models M Batchkarov, T Kober, J Reffin, J Weeds, D Weir 1st Workshop on Evaluating Vector Space Representations for NLP, 7-12, 2016 | 80 | 2016 |
| Aligning Packed Dependency Trees: a theory of composition for distributional semantics D Weir, J Weeds, J Reffin, T Kober Computational Linguistics 42 (4), 2016 | 39 | 2016 |
| Star: A schema-guided dialog dataset for transfer learning JEM Mosig, S Mehri, T Kober arXiv preprint arXiv:2010.11853, 2020 | 34 | 2020 |
| Data augmentation for hypernymy detection T Kober, J Weeds, L Bertolini, D Weir Proceedings of the 16th Conference of the European Chapter of the …, 2021 | 25 | 2021 |
| Temporal and Aspectual Entailment T Kober, S Bijl de Vroe, M Steedman Proceedings of the International Conference on Computational Semantics (IWCS …, 2019 | 24 | 2019 |
| Improving Sparse Word Representations with Distributional Inference for Semantic Composition T Kober, J Weeds, J Reffin, D Weir Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016 | 16 | 2016 |
| Aspectuality Across Genre: A Distributional Semantics Approach T Kober, M Alikhani, M Stone, M Steedman Proceedings of the 28th International Conference on Computational Linguistics, 2020 | 13 | 2020 |
| Going beyond T-SNE: Exposing whatlies in text embeddings V Warmerdam, T Kober, R Tatman Proceedings of second workshop for nlp open source software (NLP-OSS), 52-60, 2020 | 10 | 2020 |
| One Representation per Word-Does it make Sense for Composition? T Kober, J Weeds, J Wilkie, J Reffin, D Weir Proceedings of the 1st Workshop on Sense, Concept and Entity Representations …, 2017 | 7 | 2017 |
| Zero-shot cross-linguistic learning of event semantics M Alikhani, T Kober, B Alhafni, Y Chen, M Inan, E Nielsen, S Raji, ... arXiv preprint arXiv:2207.02356, 2022 | 4 | 2022 |
| Improving semantic composition with offset inference T Kober, J Weeds, J Reffin, D Weir Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 4 | 2017 |
| Inferring unobserved co-occurrence events in Anchored Packed Trees T Kober University of Sussex, 2018 | 2 | 2018 |
| When a Red Herring is Not a Red Herring: Using Compositional Methods to Detect Non-Compositional Phrases J Weeds, T Kober, J Reffin, D Weir Proceedings of the 15th Conference of the European Chapter of the …, 2017 | 2 | 2017 |
| Optimising Agile Social Media Analysis T Kober, D Weir Proceedings of the 6th Workshop on Computational Approaches to Subjectivity …, 2015 | 2 | 2015 |
| Going beyond t-sne: Exposing\texttt {whatlies} in text embeddings VD Warmerdam, T Kober, R Tatman arXiv preprint arXiv:2009.02113, 2020 | 1 | 2020 |
| Retrieve, Annotate, Evaluate, Repeat: Leveraging Multimodal LLMs for Large-Scale Product Retrieval Evaluation K Hosseini, T Kober, J Krapac, R Vollgraf, W Cheng, AP Ramallo arXiv preprint arXiv:2409.11860, 2024 | | 2024 |
| What should I wear to a party in a Greek taverna? Evaluation for Conversational Agents in the Fashion Domain A Maronikolakis, AP Ramallo, W Cheng, T Kober arXiv preprint arXiv:2408.08907, 2024 | | 2024 |
| Scaling Semi-Supervised Multinomial Naıve Bayes TH Kober University of Sussex, 2014 | | 2014 |
| Tense and Aspect in Distributional Semantic Vector Space Models T Kober | | |
David WeirUniversity of SussexVerified email at sussex.ac.uk
