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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 Hits 1 – 12 of 12 1 Analysis of Language Change in Collaborative Instruction Following ... Effenberger, Anna; Yan, Eva; Singh, Rhia. - : University of Massachusetts Amherst, 2022 BASE Show details 2 Analysis of Language Change in Collaborative Instruction Following Effenberger, Anna; Yan, Eva; Singh, Rhia... In: Proceedings of the Society for Computation in Linguistics (2022) BASE Show details 3 Analysis of Language Change in Collaborative Instruction Following ... Effenberger, Anna; Yan, Eva; Singh, Rhia. - : arXiv, 2021 BASE Show details 4 Analysis of Language Change in Collaborative Instruction Following ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Artzi, Yoav; Effenberger, Anna. - : Underline Science Inc., 2021 BASE Show details 5 Continual Learning for Grounded Instruction Generation by Observing Human Following Behavior ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Artzi, Yoav; Kojima, Noriyuki. - : Underline Science Inc., 2021 BASE Show details 6 Evaluating Models' Local Decision Boundaries via Contrast Sets ... Gardner, Matt; Artzi, Yoav; Basmova, Victoria. - : arXiv, 2020 BASE Show details 7 What is Learned in Visually Grounded Neural Syntax Acquisition ... Kojima, Noriyuki; Averbuch-Elor, Hadar; Rush, Alexander M.; Artzi, Yoav. - : arXiv, 2020 Abstract: Visual features are a promising signal for learning bootstrap textual models. However, blackbox learning models make it difficult to isolate the specific contribution of visual components. In this analysis, we consider the case study of the Visually Grounded Neural Syntax Learner (Shi et al., 2019), a recent approach for learning syntax from a visual training signal. By constructing simplified versions of the model, we isolate the core factors that yield the model's strong performance. Contrary to what the model might be capable of learning, we find significantly less expressive versions produce similar predictions and perform just as well, or even better. We also find that a simple lexical signal of noun concreteness plays the main role in the model's predictions as opposed to more complex syntactic reasoning. ... : In ACL 2020 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2005.01678 https://arxiv.org/abs/2005.01678 BASE Hide details 8 A Corpus for Reasoning About Natural Language Grounded in Photographs ... Suhr, Alane; Zhou, Stephanie; Zhang, Ally. - : arXiv, 2018 BASE Show details 9 Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments ... Chen, Howard; Suhr, Alane; Misra, Dipendra. - : arXiv, 2018 BASE Show details 10 Mapping Instructions and Visual Observations to Actions with Reinforcement Learning ... Misra, Dipendra; Langford, John; Artzi, Yoav. - : arXiv, 2017 BASE Show details 11 Situated Learning and Understanding of Natural Language Artzi, Yoav. - 2015 BASE Show details 12 Learning to Automatically Solve Algebra Word Problems Kushman, Nate; Artzi, Yoav; Zettlemoyer, Luke... In: MIT web domain (2014) BASE Show details

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