Publication

Found 56 results
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A
Yaari, A. et al. The Aligned Multimodal Movie Treebank: An audio, video, dependency-parse treebank. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (2022).
Berzak, Y., Huang, Y., Barbu, A., Korhonen, A. & Katz, B. Anchoring and Agreement in Syntactic Annotations. (2016).PDF icon CBMM-Memo-055.pdf (768.54 KB)
Berzak, Y., Katz, B. & Levy, R. Assessing Language Proficiency from Eye Movements in Reading. 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2018). at <http://naacl2018.org/>PDF icon 1804.07329.pdf (350.43 KB)
B
Wang, C. et al. BrainBERT: Self-supervised representation learning for Intracranial Electrodes. International Conference on Learning Representations (2023). at <https://openreview.net/forum?id=xmcYx_reUn6>PDF icon 985_brainbert_self_supervised_repr.pdf (9.71 MB)
C
Kuo, Y. - L., Katz, B. & Barbu, A. Compositional Networks Enable Systematic Generalization for Grounded Language Understanding. (2021).PDF icon CBMM-Memo-129.pdf (1.2 MB)
Kuo, Y. - L., Barbu, A. & Katz, B. Compositional RL Agents That Follow Language Commands in Temporal Logic. (2021).PDF icon CBMM-Memo-127.pdf (2.12 MB)
Kuo, Y. - L., Katz, B. & Barbu, A. Compositional RL Agents That Follow Language Commands in Temporal Logic. Frontiers in Robotics and AI 8, (2021).PDF icon frobt-08-689550.pdf (1.57 MB)
Berzak, Y., Reichart, R. & Katz, B. Contrastive Analysis with Predictive Power: Typology Driven Estimation of Grammatical Error Distributions in ESL. Nineteenth Conference on Computational Natural Language Learning (CoNLL), Beijing, China (2015).
Berzak, Y., Reichart, R. & Katz, B. Contrastive Analysis with Predictive Power: Typology Driven Estimation of Grammatical Error Distributions in ESL. (2016).PDF icon memo-50.pdf (493.74 KB)
D
Kuo, Y. - L., Katz, B. & Barbu, A. Deep Compositional Robotic Planners that Follow Natural Language Commands. Workshop on Visually Grounded Interaction and Language (ViGIL) at the Thirty-third Annual Conference on Neural Information Processing Systems (NeurIPS), (2019). at <https://vigilworkshop.github.io/>
Kuo, Y. - L., Katz, B. & Barbu, A. Deep compositional robotic planners that follow natural language commands . International Conference on Robotics and Automation (ICRA) (2020).
Kuo, Y. - L., Katz, B. & Barbu, A. Deep compositional robotic planners that follow natural language commands. (2020).PDF icon CBMM-Memo-124.pdf (1.03 MB)
Kuo, Y. - L., Barbu, A. & Katz, B. Deep sequential models for sampling-based planning. The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018) (2018). doi:10.1109/IROS.2018.8593947PDF icon kuo2018planning.pdf (637.67 KB)
Barbu, A., Banda, D. & Katz, B. Deep video-to-video transformations for accessibility with an application to photosensitivity. Pattern Recognition Letters (2019). doi:10.1016/j.patrec.2019.01.019
Berzak, Y., Barbu, A., Harari, D., Katz, B. & Ullman, S. Do You See What I Mean? Visual Resolution of Linguistic Ambiguities. Conference on Empirical Methods in Natural Language Processing, Lisbon, Portugal. (2015).
Berzak, Y., Barbu, A., Harari, D., Katz, B. & Ullman, S. Do You See What I Mean? Visual Resolution of Linguistic Ambiguities. (2016).PDF icon memo-51.pdf (2.74 MB)
E
Kuo, Y. - L., Katz, B. & Barbu, A. Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2020). doi:10.1109/IROS45743.2020.9341325
Kuo, Y. - L., Katz, B. & Barbu, A. Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas. (2020).PDF icon CBMM-Memo-125.pdf (2.12 MB)
G
Ross, C., Barbu, A., Berzak, Y., Myanganbayar, B. & Katz, B. Grounding language acquisition by training semantic parsersusing captioned videos. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018), (2018). at <http://aclweb.org/anthology/D18-1285>PDF icon Ross-et-al_ACL2018_Grounding language acquisition by training semantic parsing using caption videos.pdf (3.5 MB)
H
Idiart, M. A. P., Villavicencio, A., Katz, B., Rennó-Costa, C. & Lisman, J. How Does the Brain Represents Language and Answers Questions? Using an AI System to Understand the Underlying Neurobiological Mechanisms. Frontiers in Computational Neuroscience 13, (2019).
I
Tejwani, R. et al. Incorporating Rich Social Interactions Into MDPs. (2022).PDF icon CBMM-Memo-133.pdf (1.68 MB)
Tejwani, R. et al. Incorporating Rich Social Interactions Into MDPs. 2022 IEEE International Conference on Robotics and Automation (ICRA)2022 International Conference on Robotics and Automation (ICRA) (2022). doi:10.1109/ICRA46639.2022.9811991
L
Berzak, Y., Barbu, A., Harari, D., Katz, B. & Ullman, S. Language and Vision Ambiguities (LAVA) Corpus. (2016). at <http://web.mit.edu/lavacorpus/>PDF icon D15-1172.pdf (2.42 MB)
Conwell, C. et al. Large-scale benchmarking of deep neural network models in mouse visual cortex reveals patterns similar to those observed in macaque visual cortex. Cosyne (2021).
Wang, C., Ross, C., Kuo, Y. - L., Katz, B. & Barbu, A. Learning a Natural-language to LTL Executable Semantic Parser for Grounded Robotics. (Proceedings of Conference on Robot Learning (CoRL-2020), 2020). at <https://corlconf.github.io/paper_385/>

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