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Jacob Andreas | Yoshua Bengio | Yonatan Bisk | Ari Holtzman | Jesse Thomason | Angeliki Lazaridou | Nicolas Pinto | Jonathan May | Joseph P. Turian | Joseph Turian | Mirella Lapata | Joyce Chai | Aleksandr Nisnevich | Yoshua Bengio | Mirella Lapata | Ari Holtzman | Angeliki Lazaridou | N. Pinto | Yonatan Bisk | Jacob Andreas | Jesse Thomason | J. Chai | Jonathan May | Aleksandr Nisnevich | Nicolas Pinto
[1] L. Auger. The Journal of the Acoustical Society of America , 1949 .
[2] I. Good. THE POPULATION FREQUENCIES OF SPECIES AND THE ESTIMATION OF POPULATION PARAMETERS , 1953 .
[3] J. R. Firth,et al. A Synopsis of Linguistic Theory, 1930-1955 , 1957 .
[4] L. Wittgenstein. The Blue and Brown Books , 1958 .
[5] Noam Chomsky,et al. वाक्यविन्यास का सैद्धान्तिक पक्ष = Aspects of the theory of syntax , 1965 .
[6] Joseph Weizenbaum,et al. ELIZA—a computer program for the study of natural language communication between man and machine , 1966, CACM.
[7] C. Cairns,et al. How Children Learn Language. , 1969 .
[8] A. Samuel,et al. Whither speech recognition? , 1969, The Journal of the Acoustical Society of America.
[9] Terry Winograd,et al. Procedures As A Representation For Data In A Computer Program For Understanding Natural Language , 1971 .
[10] Terry Winograd,et al. Understanding natural language , 1974 .
[11] Susan Ervin-Tripp,et al. SOME STRATEGIES FOR THE FIRST TWO YEARS , 1973 .
[12] George Lakoff,et al. Hedges: A study in meaning criteria and the logic of fuzzy concepts , 1973, J. Philos. Log..
[13] Eugene Charniak. Framed PAINTING: The Representation of a Common Sense Knowledge Fragment , 1977 .
[14] Eugene Charniak,et al. Framed PAINTING: The Representation of a Common Sense Knowledge Fragment , 1977, Cogn. Sci..
[15] Roger C. Schank,et al. Scripts, plans, goals and understanding: an inquiry into human knowledge structures , 1978 .
[16] D. Premack,et al. Does the chimpanzee have a theory of mind? , 1978, Behavioral and Brain Sciences.
[17] A. M. Turing,et al. Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.
[18] Massimo Piattelli-Palmarini,et al. Language and Learning: The Debate Between Jean Piaget and Noam Chomsky , 1980 .
[19] Noam Chomsky,et al. Lectures on Government and Binding , 1981 .
[20] Gerald DeJong,et al. Generalizations Based on Explanations , 1981, IJCAI.
[21] Zellig S. Harris,et al. Distributional Structure , 1954 .
[22] J. Sachs,et al. Language learning with restricted input: Case studies of two hearing children of deaf parents , 1981, Applied Psycholinguistics.
[23] G. Lakoff,et al. Metaphors We Live by , 1982 .
[24] Gerald DeJong,et al. Learning Schemata for Natural Language Processing , 1985, IJCAI.
[25] Teuvo Kohonen,et al. Self-Organization and Associative Memory , 1988 .
[26] Susan T. Dumais,et al. Improving information retrieval using latent semantic indexing , 1988 .
[27] Richard A. Harshman,et al. Indexing by Latent Semantic Analysis , 1990, J. Am. Soc. Inf. Sci..
[28] Geoffrey E. Hinton,et al. Distributed Representations , 1986, The Philosophy of Artificial Intelligence.
[29] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[30] Geoffrey E. Hinton. Preface to the Special Issue on Connectionist Symbol Processing , 1990 .
[31] Geoffrey E. Hinton. Tensor Product Variable Binding and the Representation of Symbolic Structures in Connectionist Systems , 1991 .
[32] G. M. Werner. Evolution of Communication in Artificial Organisms, Artifial Life II , 1991 .
[33] Robert L. Mercer,et al. Class-Based n-gram Models of Natural Language , 1992, CL.
[34] J. Holmes,et al. An introduction to sociolinguistics , 1987 .
[35] Elinor Ochs. Constructing Social Identity: A Language Socialization Perspective , 1993 .
[36] Beatrice Santorini,et al. Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.
[37] Robin I. M. Dunbar. Coevolution of neocortical size, group size and language in humans , 1993, Behavioral and Brain Sciences.
[38] Risto Miikkulainen,et al. SARDNET: A Self-Organizing Feature Map for Sequences , 1994, NIPS.
[39] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[40] Hermann Ney,et al. Improved backing-off for M-gram language modeling , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.
[41] D. Lewkowicz,et al. A dynamic systems approach to the development of cognition and action. , 2007, Journal of cognitive neuroscience.
[42] Dare A. Baldwin,et al. Infants' reliance on a social criterion for establishing word-object relations. , 1996, Child development.
[43] M. Tomasello,et al. Social cognition, joint attention, and communicative competence from 9 to 15 months of age. , 1998, Monographs of the Society for Research in Child Development.
[44] F ChenStanley,et al. An Empirical Study of Smoothing Techniques for Language Modeling , 1996, ACL.
[45] Terrence J. Sejnowski,et al. Unsupervised Learning , 2018, Encyclopedia of GIS.
[46] Yoshua Bengio,et al. A Neural Probabilistic Language Model , 2003, J. Mach. Learn. Res..
[47] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[48] Susan J. Hespos,et al. Conceptual precursors to language , 2004, Nature.
[49] Michael Gasser,et al. The Development of Embodied Cognition: Six Lessons from Babies , 2005, Artificial Life.
[50] M. Tomasello. Constructing a Language , 2005 .
[51] Siobhan Chapman. Logic and Conversation , 2005 .
[52] Peter Wiemer-Hastings,et al. Latent semantic analysis , 2004, Annu. Rev. Inf. Sci. Technol..
[53] Yee Whye Teh,et al. A Hierarchical Bayesian Language Model Based On Pitman-Yor Processes , 2006, ACL.
[54] Benjamin Kuipers,et al. Walk the Talk: Connecting Language, Knowledge, and Action in Route Instructions , 2006, AAAI.
[55] David DeVault,et al. Societal Grounding Is Essential to Meaningful Language Use , 2006, AAAI.
[56] S. Harnad. Symbol grounding problem , 1991, Scholarpedia.
[57] Tom M. Mitchell,et al. The Need for Biases in Learning Generalizations , 2007 .
[58] Andrés Montoyo,et al. Advances on natural language processing , 2007, Data Knowl. Eng..
[59] Raymond J. Mooney,et al. Learning to sportscast: a test of grounded language acquisition , 2008, ICML '08.
[60] Raymond J. Mooney,et al. Learning to Connect Language and Perception , 2008, AAAI.
[61] L. Barsalou. Grounded cognition. , 2008, Annual review of psychology.
[62] Jason Weston,et al. A unified architecture for natural language processing: deep neural networks with multitask learning , 2008, ICML '08.
[63] Mark Steedman,et al. Last Words: On Becoming a Discipline , 2008, CL.
[64] C. Frith. Social cognition , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.
[65] Katrin Erk,et al. A Structured Vector Space Model for Word Meaning in Context , 2008, EMNLP.
[66] 蒋家义. How to Do Things with Words之脉络分析 , 2009 .
[67] Csr Young,et al. How to Do Things With Words , 2009 .
[68] Silvia Bernardini,et al. The WaCky wide web: a collection of very large linguistically processed web-crawled corpora , 2009, Lang. Resour. Evaluation.
[69] David D. Cox,et al. A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation , 2009, PLoS Comput. Biol..
[70] Patrick Pantel,et al. From Frequency to Meaning: Vector Space Models of Semantics , 2010, J. Artif. Intell. Res..
[71] Stephanie Rosenthal,et al. An effective personal mobile robot agent through symbiotic human-robot interaction , 2010, AAMAS.
[72] Yansong Feng,et al. Topic Models for Image Annotation and Text Illustration , 2010, HLT-NAACL.
[73] M. Guasti. How Children Learn the Meanings of Words , 2010 .
[74] U. Hasson,et al. Speaker–listener neural coupling underlies successful communication , 2010, Proceedings of the National Academy of Sciences.
[75] Yoshua Bengio,et al. Word Representations: A Simple and General Method for Semi-Supervised Learning , 2010, ACL.
[76] Cyrus Rashtchian,et al. Every Picture Tells a Story: Generating Sentences from Images , 2010, ECCV.
[77] Estevam R. Hruschka,et al. Toward an Architecture for Never-Ending Language Learning , 2010, AAAI.
[78] Kenneth Ward Church,et al. A Pendulum Swung too Far , 2011 .
[79] J. Brockmeier,et al. The Role of Language Games in Children's Understanding of Mental States: A Training Study , 2011 .
[80] Matthew R. Walter,et al. Understanding Natural Language Commands for Robotic Navigation and Mobile Manipulation , 2011, AAAI.
[81] Andrew Y. Ng,et al. Semantic Compositionality through Recursive Matrix-Vector Spaces , 2012, EMNLP.
[82] Michael C. Frank,et al. Predicting Pragmatic Reasoning in Language Games , 2012, Science.
[83] Karl Stratos,et al. Midge: Generating Image Descriptions From Computer Vision Detections , 2012, EACL.
[84] Gemma Boleda,et al. Distributional Semantics in Technicolor , 2012, ACL.
[85] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[86] Yuval Tassa,et al. MuJoCo: A physics engine for model-based control , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[87] Bernt Schiele,et al. Grounding Action Descriptions in Videos , 2013, TACL.
[88] Matthew R. Walter,et al. Learning Semantic Maps from Natural Language Descriptions , 2013, Robotics: Science and Systems.
[89] M. Engelmann. The Philosophical Investigations , 2013 .
[90] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[91] R. Barr. Memory Constraints on Infant Learning From Picture Books, Television, and Touchscreens , 2013 .
[92] D. Hofstadter,et al. Surfaces and Essences: Analogy as the Fuel and Fire of Thinking , 2013 .
[93] Cliff Fitzgerald,et al. Developing baxter , 2013, 2013 IEEE Conference on Technologies for Practical Robot Applications (TePRA).
[94] Wanxiang Che,et al. Learning Semantic Hierarchies via Word Embeddings , 2014, ACL.
[95] Connor Schenck,et al. Learning relational object categories using behavioral exploration and multimodal perception , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[96] Elia Bruni,et al. Multimodal Distributional Semantics , 2014, J. Artif. Intell. Res..
[97] Carina Silberer,et al. Learning Grounded Meaning Representations with Autoencoders , 2014, ACL.
[98] G. Zipf. Selected Studies of the Principle of Relative Frequency in Language , 2014 .
[99] G. Vigliocco,et al. Language as a multimodal phenomenon: implications for language learning, processing and evolution , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.
[100] Yunyi Jia,et al. Back to the Blocks World: Learning New Actions through Situated Human-Robot Dialogue , 2014, SIGDIAL Conference.
[101] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[102] Ross A. Knepper,et al. Asking for Help Using Inverse Semantics , 2014, Robotics: Science and Systems.
[103] Changsong Liu,et al. Learning to Mediate Perceptual Differences in Situated Human-Robot Dialogue , 2015, AAAI.
[104] Xiaogang Wang,et al. Deep Learning Face Attributes in the Wild , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[105] Yonatan Bisk,et al. Probing the Linguistic Strengths and Limitations of Unsupervised Grammar Induction , 2015, ACL.
[106] Margaret Mitchell,et al. VQA: Visual Question Answering , 2015, International Journal of Computer Vision.
[107] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[108] Dan Roth,et al. Solving Hard Coreference Problems , 2019, NAACL.
[109] Joelle Pineau,et al. How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation , 2016, EMNLP.
[110] Roger Levy,et al. Pragmatic reasoning through semantic inference , 2016, Semantics and Pragmatics.
[111] Wei-Lun Chao,et al. An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild , 2016, ECCV.
[112] Changsong Liu,et al. Collaborative Language Grounding Toward Situated Human-Robot Dialogue , 2017, AI Mag..
[113] Angeliki Lazaridou,et al. The red one!: On learning to refer to things based on discriminative properties , 2016, ACL.
[114] Donald Perlis. Five Dimensions of Reasoning in the Wild , 2016, AAAI.
[115] Sandro Pezzelle,et al. The LAMBADA dataset: Word prediction requiring a broad discourse context , 2016, ACL.
[116] Dan Klein,et al. Reasoning about Pragmatics with Neural Listeners and Speakers , 2016, EMNLP.
[117] Michael S. Bernstein,et al. Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations , 2016, International Journal of Computer Vision.
[118] Ali Farhadi,et al. XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks , 2016, ECCV.
[119] Ali Farhadi,et al. Situation Recognition: Visual Semantic Role Labeling for Image Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[120] Peter Stone,et al. Learning Multi-Modal Grounded Linguistic Semantics by Playing "I Spy" , 2016, IJCAI.
[121] Cristian Danescu-Niculescu-Mizil,et al. Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions , 2016, WWW.
[122] Ali Farhadi,et al. "What Happens If..." Learning to Predict the Effect of Forces in Images , 2016, ECCV.
[123] Alexandre Campeau-Lecours,et al. Kinova Modular Robot Arms for Service Robotics Applications , 2017, Int. J. Robotics Appl. Technol..
[124] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[125] Jon Gauthier,et al. Are Distributional Representations Ready for the Real World? Evaluating Word Vectors for Grounded Perceptual Meaning , 2017, RoboNLP@ACL.
[126] Joelle Pineau,et al. A Deep Reinforcement Learning Chatbot , 2017, ArXiv.
[127] Peter Stone,et al. Opportunistic Active Learning for Grounding Natural Language Descriptions , 2017, CoRL.
[128] Yann Dauphin,et al. Deal or No Deal? End-to-End Learning of Negotiation Dialogues , 2017, EMNLP.
[129] Wei-Lun Chao,et al. Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[130] Desmond Elliott,et al. Imagination Improves Multimodal Translation , 2017, IJCNLP.
[131] Richard Socher,et al. Learned in Translation: Contextualized Word Vectors , 2017, NIPS.
[132] Ling-Yi Lin,et al. Effect of Touch Screen Tablet Use on Fine Motor Development of Young Children , 2017, Physical & occupational therapy in pediatrics.
[133] Jason Weston,et al. Learning End-to-End Goal-Oriented Dialog , 2016, ICLR.
[134] Alexander Peysakhovich,et al. Multi-Agent Cooperation and the Emergence of (Natural) Language , 2016, ICLR.
[135] Shaohua Yang,et al. Language to Action: Towards Interactive Task Learning with Physical Agents , 2018, IJCAI.
[136] Nicholas Roy,et al. Efficient grounding of abstract spatial concepts for natural language interaction with robot platforms , 2018, Int. J. Robotics Res..
[137] Omer Levy,et al. Annotation Artifacts in Natural Language Inference Data , 2018, NAACL.
[138] Thien Huu Nguyen,et al. BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop , 2018, ArXiv.
[139] Daniel Marcu,et al. Learning Interpretable Spatial Operations in a Rich 3D Blocks World , 2017, AAAI.
[140] Luke S. Zettlemoyer,et al. Deep Contextualized Word Representations , 2018, NAACL.
[141] Yoav Goldberg,et al. Breaking NLI Systems with Sentences that Require Simple Lexical Inferences , 2018, ACL.
[142] Mark O. Riedl,et al. Event Representations for Automated Story Generation with Deep Neural Nets , 2017, AAAI.
[143] Percy Liang,et al. Know What You Don’t Know: Unanswerable Questions for SQuAD , 2018, ACL.
[144] Cynthia Matuszek,et al. Grounded Language Learning: Where Robotics and NLP Meet , 2018, IJCAI.
[145] James R. Glass,et al. Jointly Discovering Visual Objects and Spoken Words from Raw Sensory Input , 2018, ECCV.
[146] Matthew J. Hausknecht,et al. TextWorld: A Learning Environment for Text-based Games , 2018, CGW@IJCAI.
[147] Omer Levy,et al. GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding , 2018, BlackboxNLP@EMNLP.
[148] Lei Zhang,et al. Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[149] Yejin Choi,et al. SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference , 2018, EMNLP.
[150] Ali Farhadi,et al. IQA: Visual Question Answering in Interactive Environments , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[151] Radu Soricut,et al. Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning , 2018, ACL.
[152] Derek Chen,et al. Decoupling Strategy and Generation in Negotiation Dialogues , 2018, EMNLP.
[153] Stephen Clark,et al. Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input , 2018, ICLR.
[154] Nazli Ikizler-Cinbis,et al. RecipeQA: A Challenge Dataset for Multimodal Comprehension of Cooking Recipes , 2018, EMNLP.
[155] Thomas L. Griffiths,et al. Evaluating Theory of Mind in Question Answering , 2018, EMNLP.
[156] Daniele Moro,et al. Multimodal Visual and Simulated Muscle Activations for Grounded Semantics of Hand-related Descriptions , 2018 .
[157] Stefan Lee,et al. Embodied Question Answering , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[158] Cordelia Schmid,et al. Learning Video Representations using Contrastive Bidirectional Transformer , 2019 .
[159] David Schlangen,et al. Language Tasks and Language Games: On Methodology in Current Natural Language Processing Research , 2019, ArXiv.
[160] Cewu Lu,et al. HAKE: Human Activity Knowledge Engine , 2019, ArXiv.
[161] Siddhartha S. Srinivasa,et al. Improving Robot Success Detection using Static Object Data , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[162] Jesse Thomason,et al. Vision-and-Dialog Navigation , 2019, CoRL.
[163] Xin Wang,et al. VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[164] Tal Linzen,et al. Quantity doesn’t buy quality syntax with neural language models , 2019, EMNLP.
[165] Zhou Yu,et al. Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good , 2019, ACL.
[166] Y-Lan Boureau,et al. Revisiting the Evaluation of Theory of Mind through Question Answering , 2019, EMNLP.
[167] Yejin Choi,et al. Social IQA: Commonsense Reasoning about Social Interactions , 2019, EMNLP 2019.
[168] Quoc V. Le,et al. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks , 2019, ICML.
[169] Cho-Jui Hsieh,et al. VisualBERT: A Simple and Performant Baseline for Vision and Language , 2019, ArXiv.
[170] Abhinav Gupta,et al. PyRobot: An Open-source Robotics Framework for Research and Benchmarking , 2019, ArXiv.
[171] Stefan Lee,et al. ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks , 2019, NeurIPS.
[172] Ali Farhadi,et al. From Recognition to Cognition: Visual Commonsense Reasoning , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[173] Hinrich Schütze,et al. Extending Machine Language Models toward Human-Level Language Understanding , 2019, ArXiv.
[174] Kevin Gimpel,et al. Visually Grounded Neural Syntax Acquisition , 2019, ACL.
[175] Lav R. Varshney,et al. CTRL: A Conditional Transformer Language Model for Controllable Generation , 2019, ArXiv.
[176] M. Shoeybi,et al. Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism , 2019, ArXiv.
[177] Ali Farhadi,et al. HellaSwag: Can a Machine Really Finish Your Sentence? , 2019, ACL.
[178] Ross B. Girshick,et al. PHYRE: A New Benchmark for Physical Reasoning , 2019, NeurIPS.
[179] Ilya Sutskever,et al. Language Models are Unsupervised Multitask Learners , 2019 .
[180] Ruslan Salakhutdinov,et al. Multimodal Transformer for Unaligned Multimodal Language Sequences , 2019, ACL.
[181] Dipanjan Das,et al. BERT Rediscovers the Classical NLP Pipeline , 2019, ACL.
[182] R Devon Hjelm,et al. Learning Representations by Maximizing Mutual Information Across Views , 2019, NeurIPS.
[183] Y-Lan Boureau,et al. Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset , 2018, ACL.
[184] David Reitter,et al. Like a Baby: Visually Situated Neural Language Acquisition , 2018, ACL.
[185] Ali Farhadi,et al. Defending Against Neural Fake News , 2019, NeurIPS.
[186] Yonatan Bisk,et al. Shifting the Baseline: Single Modality Performance on Visual Navigation & QA , 2018, NAACL.
[187] Jason Weston,et al. Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack , 2019, EMNLP.
[188] David Schlangen,et al. Grounded Agreement Games: Emphasizing Conversational Grounding in Visual Dialogue Settings , 2019, ArXiv.
[189] Yoav Artzi,et al. Executing Instructions in Situated Collaborative Interactions , 2019, EMNLP.
[190] Cordelia Schmid,et al. VideoBERT: A Joint Model for Video and Language Representation Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[191] Gabriel Ilharco,et al. Large-Scale Representation Learning from Visually Grounded Untranscribed Speech , 2019, CoNLL.
[192] Diyi Yang,et al. Let’s Make Your Request More Persuasive: Modeling Persuasive Strategies via Semi-Supervised Neural Nets on Crowdfunding Platforms , 2019, NAACL.
[193] Yoav Artzi,et al. A Corpus for Reasoning about Natural Language Grounded in Photographs , 2018, ACL.
[194] Michael I. Jordan,et al. Artificial Intelligence—The Revolution Hasn’t Happened Yet , 2019, Issue 1.
[195] Abhijit Mahabal,et al. How Large Are Lions? Inducing Distributions over Quantitative Attributes , 2019, ACL.
[196] Ashish Vaswani,et al. Stand-Alone Self-Attention in Vision Models , 2019, NeurIPS.
[197] Omer Levy,et al. SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems , 2019, NeurIPS.
[198] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[199] Yiming Yang,et al. XLNet: Generalized Autoregressive Pretraining for Language Understanding , 2019, NeurIPS.
[200] Louis-Philippe Morency,et al. Social-IQ: A Question Answering Benchmark for Artificial Social Intelligence , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[201] Ross A. Knepper,et al. Learning to Map Natural Language Instructions to Physical Quadcopter Control using Simulated Flight , 2019, CoRL.
[202] Cordelia Schmid,et al. Contrastive Bidirectional Transformer for Temporal Representation Learning , 2019, ArXiv.
[203] Emily M. Bender,et al. Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data , 2020, ACL.
[204] Yejin Choi,et al. PIQA: Reasoning about Physical Commonsense in Natural Language , 2019, AAAI.
[205] James R. Glass,et al. Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech , 2019, ICLR.
[206] S. Kolassa. Two Cheers for Rebooting AI: Building Artificial Intelligence We Can Trust , 2020 .
[207] Alexander Hauptmann,et al. Unsupervised Multimodal Neural Machine Translation with Pseudo Visual Pivoting , 2020, ACL.
[208] Peter Stone,et al. Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog , 2020, J. Artif. Intell. Res..
[209] Jason J. Corso,et al. Unified Vision-Language Pre-Training for Image Captioning and VQA , 2019, AAAI.
[210] Harry Shum,et al. The Design and Implementation of XiaoIce, an Empathetic Social Chatbot , 2018, CL.
[211] Mark Chen,et al. Language Models are Few-Shot Learners , 2020, NeurIPS.
[212] Christopher D. Manning,et al. Towards Ecologically Valid Research on Language User Interfaces , 2020, ArXiv.
[213] Kevin Gimpel,et al. ALBERT: A Lite BERT for Self-supervised Learning of Language Representations , 2019, ICLR.
[214] Reut Tsarfaty,et al. Evaluating NLP Models via Contrast Sets , 2020, ArXiv.
[215] Yejin Choi,et al. Evaluating Machines by their Real-World Language Use , 2020, ArXiv.
[216] Zachary Chase Lipton,et al. Learning the Difference that Makes a Difference with Counterfactually-Augmented Data , 2019, ICLR.
[217] Hadas Kress-Gazit,et al. Robots That Use Language , 2020, Annu. Rev. Control. Robotics Auton. Syst..
[218] Ramon Sanabria,et al. Looking Enhances Listening: Recovering Missing Speech Using Images , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[219] Yejin Choi,et al. The Curious Case of Neural Text Degeneration , 2019, ICLR.
[220] Quoc V. Le,et al. Towards a Human-like Open-Domain Chatbot , 2020, ArXiv.
[221] Tal Linzen,et al. How Can We Accelerate Progress Towards Human-like Linguistic Generalization? , 2020, ACL.
[222] Eugene Kharitonov,et al. Compositionality and Generalization In Emergent Languages , 2020, ACL.
[223] Leonidas J. Guibas,et al. SAPIEN: A SimulAted Part-Based Interactive ENvironment , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[224] Luke Zettlemoyer,et al. ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).