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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 26 1 Trajectory Prediction with Linguistic Representations Kuo, Yen-Ling; Huang, Xin; Barbu, Andrei. - : Center for Brains, Minds and Machines (CBMM), International Conference on Robotics and Automation (ICRA), 2022 BASE Show details 2 Compositional Networks Enable Systematic Generalization for Grounded Language Understanding Kuo, Yen-Ling; Katz, Boris; Barbu, Andrei. - : Center for Brains, Minds and Machines (CBMM), Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021 BASE Show details 3 Trajectory Prediction with Linguistic Representations ... Kuo, Yen-Ling; Huang, Xin; Barbu, Andrei. - : arXiv, 2021 BASE Show details 4 Measuring Social Biases in Grounded Vision and Language Embeddings ... NAACL 2021 2021; Barbu, Andrei; Katz, Boris. - : Underline Science Inc., 2021 BASE Show details 5 Compositional Networks Enable Systematic Generalization for Grounded Language Understanding ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Barbu, Andrei; Katz, Boris. - : Underline Science Inc., 2021 BASE Show details 6 Measuring Social Biases in Grounded Vision and Language Embeddings Ross, Candace; Barbu, Andrei; Katz, Boris. - : Center for Brains, Minds and Machines (CBMM), Annual Conference of the North American Chapter of the Association for Computational Linguistics (HLT/NAACL), 2021 BASE Show details 7 Learning a natural-language to LTL executable semantic parser for grounded robotics Wang, Christopher; Ross, Candace; Kuo, Yen-Ling. - : Center for Brains, Minds and Machines (CBMM), Conference on Robot Learning (CoRL), 2020 BASE Show details 8 Compositional Networks Enable Systematic Generalization for Grounded Language Understanding ... Kuo, Yen-Ling; Katz, Boris; Barbu, Andrei. - : arXiv, 2020 BASE Show details 9 Learning a natural-language to LTL executable semantic parser for grounded robotics ... Wang, Christopher; Ross, Candace; Kuo, Yen-Ling. - : arXiv, 2020 BASE Show details 10 Measuring Social Biases in Grounded Vision and Language Embeddings ... Ross, Candace; Katz, Boris; Barbu, Andrei. - : arXiv, 2020 BASE Show details 11 Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas Kuo, Yen-Ling; Katz, Boris; Barbu, Andrei. - : Center for Brains, Minds and Machines (CBMM), The Ninth International Conference on Learning Representations (ICLR), 2020 BASE Show details 12 Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context ... Paul, Rohan; Barbu, Andrei; Felshin, Sue. - : arXiv, 2018 BASE Show details 13 Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context Paul, Rohan; Barbu, Andrei; Felshin, Sue... In: Other repository (2018) BASE Show details 14 Do You See What I Mean? Visual Resolution of Linguistic Ambiguities Berzak, Yevgeni; Barbu, Andrei; Harari, Daniel; Katz, Boris; Ullman, Shimon. - : Center for Brains, Minds and Machines (CBMM), arXiv, 2016 Abstract: Understanding language goes hand in hand with the ability to integrate complex contextual information obtained via perception. In this work, we present a novel task for grounded language understanding: disambiguating a sentence given a visual scene which depicts one of the possible interpretations of that sentence. To this end, we introduce a new multimodal corpus containing ambiguous sentences, representing a wide range of syntactic, semantic and discourse ambiguities, coupled with videos that visualize the different interpretations for each sentence. We address this task by extending a vision model which determines if a sentence is depicted by a video. We demonstrate how such a model can be adjusted to recognize different interpretations of the same underlying sentence, allowing to disambiguate sentences in a unified fashion across the different ambiguity types. ; This work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF – 1231216. Keyword: Computer Language; Computer vision; Language understanding URL: http://hdl.handle.net/1721.1/103400 BASE Hide details 15 Anchoring and Agreement in Syntactic Annotations Berzak, Yevgeni; Huang, Yan; Barbu, Andrei. - : Center for Brains, Minds and Machines (CBMM), arXiv, 2016 BASE Show details 16 Do You See What I Mean? Visual Resolution of Linguistic Ambiguities ... Berzak, Yevgeni; Barbu, Andrei; Harari, Daniel. - : arXiv, 2016 BASE Show details 17 Seeing What You’re Told: Sentence-Guided Activity Recognition In Video Siddharth, Narayanaswamy; Barbu, Andrei; Siskind, Jeffrey Mark. - : Center for Brains, Minds and Machines (CBMM), arXiv, 2014 BASE Show details 18 The Compositional Nature of Event Representations in the Human Brain Barbu, Andrei; Narayanaswamy, Siddharth; Xiong, Caiming. - : Center for Brains, Minds and Machines (CBMM), arXiv, 2014 BASE Show details 19 Video In Sentences Out ... Barbu, Andrei; Bridge, Alexander; Burchill, Zachary. - : arXiv, 2014 BASE Show details 20 Saying What You're Looking For: Linguistics Meets Video Search ... Barbu, Andrei; Siddharth, N.; Siskind, Jeffrey Mark. - : arXiv, 2013 BASE Show details Page: 1 2

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