Publications

CBMM Memos were established in 2014 as a mechanism for our center to share research results with the wider scientific community. Click here to read more about the memos and to see a full list of the memos.

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Filters: Author is Andrei Barbu [Clear All Filters]

Book Chapter

Barbu, A. et al. Computer Vision – ECCV 2014, Lecture Notes in Computer Science 8693, 612–627 (Springer International Publishing, 2014).

CBMM Memos

Amir, N. et al. Abstracts of the 2014 Brains, Minds, and Machines Summer Course. (2014).

CBMM-Memo-024.pdf (2.86 MB)

Berzak, Y., Huang, Y., Barbu, A., Korhonen, A. & Katz, B. Anchoring and Agreement in Syntactic Annotations. (2016).

CBMM-Memo-055.pdf (768.54 KB)

Barbu, A. et al. The Compositional Nature of Event Representations in the Human Brain. (2014).

CBMM Memo 011.pdf (3.95 MB)

Kuo, Y. - L., Katz, B. & Barbu, A. Compositional Networks Enable Systematic Generalization for Grounded Language Understanding. (2021).

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).

CBMM-Memo-127.pdf (2.12 MB)

Kuo, Y. - L., Katz, B. & Barbu, A. Deep compositional robotic planners that follow natural language commands. (2020).

CBMM-Memo-124.pdf (1.03 MB)

Berzak, Y., Barbu, A., Harari, D., Katz, B. & Ullman, S. Do You See What I Mean? Visual Resolution of Linguistic Ambiguities. (2016).

memo-51.pdf (2.74 MB)

Kuo, Y. - L., Katz, B. & Barbu, A. Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas. (2020).

CBMM-Memo-125.pdf (2.12 MB)

Tejwani, R. et al. Incorporating Rich Social Interactions Into MDPs. (2022).

CBMM-Memo-133.pdf (1.68 MB)

Wang, C., Ross, C., Kuo, Y. - L., Katz, B. & Barbu, A. Learning a natural-language to LTL executable semantic parser for grounded robotics. (2020). doi:https://doi.org/10.48550/arXiv.2008.03277

CBMM-Memo-122.pdf (1.03 MB)

Ross, C., Barbu, A. & Katz, B. Measuring Social Biases in Grounded Vision and Language Embeddings. (2021).

CBMM-Memo-126.pdf (1.32 MB)

Conwell, C. et al. Neural Regression, Representational Similarity, Model Zoology Neural Taskonomy at Scale in Rodent Visual Cortex. (2021).

CBMM-Memo-131.pdf (9.37 MB)

Myanganbayar, B. et al. Partially Occluded Hands: A challenging new dataset for single-image hand pose estimation. (2018).

CBMM-Memo-097.pdf (8.53 MB)

Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception. (2021).

CBMM-Memo-123.pdf (3.08 MB)

Barbu, A. et al. Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions. (2014).

CBMM Memo 012.pdf (678.95 KB)

Siddharth, N., Barbu, A. & Siskind, J. Mark. Seeing What You’re Told: Sentence-Guided Activity Recognition In Video. (2014).

CBMM-Memo-006.pdf (1.2 MB)

Tejwani, R., Kuo, Y. - L., Shu, T., Katz, B. & Barbu, A. Social Interactions as Recursive MDPs. (2021).

CBMM-Memo-130.pdf (1.52 MB)

Palmer, I., Rouditchenko, A., Barbu, A., Katz, B. & Glass, J. Spoken ObjectNet: A Bias-Controlled Spoken Caption Dataset. (2021).

CBMM-Memo-128.pdf (2.91 MB)

Kuo, Y. - L. et al. Trajectory Prediction with Linguistic Representations. (2022).

CBMM-Memo-132.pdf (1.15 MB)

Conference Paper

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).

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., 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.2018.8593947

kuo2018planning.pdf (637.67 KB)

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).

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

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