{"list":"other","total":101,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"id":"1405.0312","title":"Microsoft COCO: Common Objects in Context","created":"2014-05-01","cited_by_count":17608},{"id":"2302.13971","title":"LLaMA: Open and Efficient Foundation Language Models","created":"2023-02-27","cited_by_count":14132},{"id":"1703.03400","title":"Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks","created":"2017-03-09","cited_by_count":4897},{"id":"1611.01144","title":"Categorical Reparameterization with Gumbel-Softmax","created":"2016-11-03","cited_by_count":2739},{"id":"1308.3432","title":"Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation","created":"2013-08-15","cited_by_count":2079},{"id":"1706.02275","title":"Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments","created":"2017-06-07","cited_by_count":1558},{"id":"2201.08239","title":"LaMDA: Language Models for Dialog Applications","created":"2022-01-20","cited_by_count":1220},{"id":"1611.00712","title":"The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables","created":"2016-11-02","cited_by_count":1148},{"id":"1605.06676","title":"Learning to Communicate with Deep Multi-Agent Reinforcement Learning","created":"2016-05-21","cited_by_count":575},{"id":"1605.07736","title":"Learning Multiagent Communication with Backpropagation","created":"2016-05-25","cited_by_count":366},{"id":"1807.01281","title":"Human-level performance in first-person multiplayer games with population-based deep reinforcement learning","created":"2018-07-03","cited_by_count":264},{"id":"1703.04908","title":"Emergence of Grounded Compositional Language in Multi-Agent Populations","created":"2017-03-15","cited_by_count":263},{"id":"1605.00459","title":"Multi30K: Multilingual English-German Image Descriptions","created":"2016-05-02","cited_by_count":250},{"id":"1802.07740","title":"Machine Theory of Mind","created":"2018-02-21","cited_by_count":226},{"id":"1709.04326","title":"Learning with Opponent-Learning Awareness","created":"2017-09-13","cited_by_count":222},{"id":"1706.05125","title":"Deal or No Deal? End-to-End Learning for Negotiation Dialogues","created":"2017-06-16","cited_by_count":209},{"id":"1810.11187","title":"TarMAC: Targeted Multi-Agent Communication","created":"2018-10-26","cited_by_count":208},{"id":"1612.07182","title":"Multi-Agent Cooperation and the Emergence of (Natural) Language","created":"2016-12-21","cited_by_count":185},{"id":"2006.02419","title":"Emergent Multi-Agent Communication in the Deep Learning Era","created":"2020-06-03","cited_by_count":170},{"id":"1906.07343","title":"Language as an Abstraction for Hierarchical Deep Reinforcement Learning","created":"2019-06-18","cited_by_count":138},{"id":"1705.11192","title":"Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols","created":"2017-05-31","cited_by_count":125},{"id":"1402.0030","title":"Neural Variational Inference and Learning in Belief Networks","created":"2014-01-31","cited_by_count":117},{"id":"2005.00955","title":"How Can We Accelerate Progress Towards Human-like Linguistic Generalization?","created":"2020-05-03","cited_by_count":114},{"id":"2004.09124","title":"Compositionality and Generalization in Emergent Languages","created":"2020-04-20","cited_by_count":103},{"id":"1804.03984","title":"Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input","created":"2018-04-11","cited_by_count":102},{"id":"2011.06619","title":"Learning Latent Representations to Influence Multi-Agent Interaction","created":"2020-11-12","cited_by_count":93},{"id":"1706.08502","title":"Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog","created":"2017-06-26","cited_by_count":86},{"id":"1902.07181","title":"Measuring Compositionality in Representation Learning","created":"2019-02-19","cited_by_count":84},{"id":"2002.01365","title":"Compositional Languages Emerge in a Neural Iterated Learning Model","created":"2020-02-04","cited_by_count":75},{"id":"1703.06585","title":"Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning","created":"2017-03-20","cited_by_count":71},{"id":"1903.05168","title":"On the Pitfalls of Measuring Emergent Communication","created":"2019-03-12","cited_by_count":71},{"id":"1604.00562","title":"Reasoning About Pragmatics with Neural Listeners and Speakers","created":"2016-04-02","cited_by_count":68},{"id":"1802.09640","title":"Modeling Others using Oneself in Multi-Agent Reinforcement Learning","created":"2018-02-26","cited_by_count":66},{"id":"2005.07064","title":"Multi-agent Communication meets Natural Language: Synergies between Functional and Structural Language Learning","created":"2020-05-14","cited_by_count":66},{"id":"1906.02403","title":"Ease-of-Teaching and Language Structure from Emergent Communication","created":"2019-06-06","cited_by_count":65},{"id":"1606.02821","title":"Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change","created":"2016-06-09","cited_by_count":63},{"id":"1804.03980","title":"Emergent Communication through Negotiation","created":"2018-04-11","cited_by_count":62},{"id":"1911.06992","title":"Learning Efficient Multi-agent Communication: An Information Bottleneck Approach","created":"2019-11-16","cited_by_count":61},{"id":"1905.12561","title":"Anti-efficient encoding in emergent communication","created":"2019-05-29","cited_by_count":59},{"id":"1904.00157","title":"Linguistic generalization and compositionality in modern artificial neural networks","created":"2019-03-30","cited_by_count":58},{"id":"2003.12694","title":"Countering Language Drift with Seeded Iterated Learning","created":"2020-03-28","cited_by_count":57},{"id":"1909.04499","title":"Countering Language Drift via Visual Grounding","created":"2019-09-10","cited_by_count":55},{"id":"1806.06464","title":"Learning Policy Representations in Multiagent Systems","created":"2018-06-17","cited_by_count":48},{"id":"1912.05676","title":"Biases for Emergent Communication in Multi-agent Reinforcement Learning","created":"2019-12-11","cited_by_count":48},{"id":"1805.07830","title":"Learning to Teach in Cooperative Multiagent Reinforcement Learning","created":"2018-05-20","cited_by_count":45},{"id":"1808.10696","title":"How agents see things: On visual representations in an emergent language game","created":"2018-08-31","cited_by_count":45},{"id":"2107.02367","title":"Discrete-Valued Neural Communication","created":"2021-07-06","cited_by_count":39},{"id":"2202.00155","title":"Fortuitous Forgetting in Connectionist Networks","created":"2022-02-01","cited_by_count":39},{"id":"1511.05176","title":"MuProp: Unbiased Backpropagation for Stochastic Neural Networks","created":"2015-11-16","cited_by_count":37},{"id":"1901.11184","title":"Human-Centered Artificial Intelligence and Machine Learning","created":"2019-01-31","cited_by_count":37},{"id":"1901.08706","title":"Emergent Linguistic Phenomena in Multi-Agent Communication Games","created":"2019-01-25","cited_by_count":36},{"id":"1809.00252","title":"Parameter Sharing Methods for Multilingual Self-Attentional Translation Models","created":"2018-09-01","cited_by_count":33},{"id":"2107.05697","title":"Few-shot Language Coordination by Modeling Theory of Mind","created":"2021-07-12","cited_by_count":32},{"id":"1912.05304","title":"Learning Agent Communication under Limited Bandwidth by Message Pruning","created":"2019-12-03","cited_by_count":31},{"id":"1804.02341","title":"Compositional Obverter Communication Learning From Raw Visual Input","created":"2018-04-06","cited_by_count":30},{"id":"1910.11424","title":"Capacity, Bandwidth, and Compositionality in Emergent Language Learning","created":"2019-10-24","cited_by_count":30},{"id":"1911.09896","title":"Continual adaptation for efficient machine communication","created":"2019-11-22","cited_by_count":28},{"id":"1910.05291","title":"The Emergence of Compositional Languages for Numeric Concepts Through Iterated Learning in Neural Agents","created":"2019-10-11","cited_by_count":26},{"id":"2106.04258","title":"Interpretable agent communication from scratch (with a generic visual processor emerging on the side)","created":"2021-06-08","cited_by_count":25},{"id":"1707.06320","title":"Learning Visually Grounded Sentence Representations","created":"2017-07-19","cited_by_count":24},{"id":"1801.09797","title":"Discrete Autoencoders for Sequence Models","created":"2018-01-29","cited_by_count":24},{"id":"2204.12982","title":"On the role of population heterogeneity in emergent communication","created":"2022-04-27","cited_by_count":24},{"id":"2106.02067","title":"Learning to Draw: Emergent Communication through Sketching","created":"2021-06-03","cited_by_count":23},{"id":"1710.06922","title":"Emergent Translation in Multi-Agent Communication","created":"2017-10-12","cited_by_count":22},{"id":"2005.05441","title":"Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive Environments","created":"2020-05-11","cited_by_count":22},{"id":"2108.01828","title":"Emergent Discrete Communication in Semantic Spaces","created":"2021-08-04","cited_by_count":20},{"id":"2203.13344","title":"Linking Emergent and Natural Languages via Corpus Transfer","created":"2022-03-24","cited_by_count":19},{"id":"1809.00549","title":"Emergence of Communication in an Interactive World with Consistent Speakers","created":"2018-09-03","cited_by_count":18},{"id":"1905.12330","title":"Word-order biases in deep-agent emergent communication","created":"2019-05-29","cited_by_count":18},{"id":"2001.03361","title":"Co-evolution of language and agents in referential games","created":"2020-01-10","cited_by_count":18},{"id":"2010.15896","title":"Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations","created":"2020-10-29","cited_by_count":18},{"id":"1904.09067","title":"Emergence of Compositional Language with Deep Generational Transmission","created":"2019-04-19","cited_by_count":17},{"id":"2001.07752","title":"Emergence of Pragmatics from Referential Game between Theory of Mind Agents","created":"2020-01-21","cited_by_count":17},{"id":"2004.03420","title":"Emergent Language Generalization and Acquisition Speed are not tied to Compositionality","created":"2020-04-07","cited_by_count":17},{"id":"2111.14210","title":"Emergent Graphical Conventions in a Visual Communication Game","created":"2021-11-28","cited_by_count":16},{"id":"1511.08130","title":"A Roadmap towards Machine Intelligence","created":"2015-11-25","cited_by_count":15},{"id":"1912.06208","title":"Shaping representations through communication: community size effect in artificial learning systems","created":"2019-12-12","cited_by_count":14},{"id":"2304.01662","title":"Cross-Domain Image Captioning with Discriminative Finetuning","created":"2023-04-04","cited_by_count":14},{"id":"1810.08647","title":"Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning","created":"2018-10-19","cited_by_count":13},{"id":"2010.10380","title":"Negotiating Team Formation Using Deep Reinforcement Learning","created":"2020-10-20","cited_by_count":13},{"id":"2011.00890","title":"Emergent Communication Pretraining for Few-Shot Machine Translation","created":"2020-11-02","cited_by_count":13},{"id":"2111.06464","title":"Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication","created":"2021-11-11","cited_by_count":12},{"id":"1905.11871","title":"Miss Tools and Mr Fruit: Emergent communication in agents learning about object affordances","created":"2019-05-28","cited_by_count":11},{"id":"2012.10776","title":"On (Emergent) Systematic Generalisation and Compositionality in Visual Referential Games with Straight-Through Gumbel-Softmax Estimator","created":"2020-12-19","cited_by_count":11},{"id":"2106.05018","title":"RLupus: Cooperation through emergent communication in The Werewolf social deduction game","created":"2021-06-09","cited_by_count":11},{"id":"2010.15058","title":"Measuring non-trivial compositionality in emergent communication","created":"2020-10-28","cited_by_count":10},{"id":"2302.08913","title":"Referential communication in heterogeneous communities of pre-trained visual deep networks","created":"2023-02-04","cited_by_count":10},{"id":"1702.05573","title":"Collaborative Deep Reinforcement Learning for Joint Object Search","created":"2017-02-18","cited_by_count":9},{"id":"2110.05422","title":"Calibrate your listeners! Robust communication-based training for pragmatic speakers","created":"2021-10-11","cited_by_count":9},{"id":"1910.06079","title":"Developmentally motivated emergence of compositional communication via template transfer","created":"2019-10-04","cited_by_count":8},{"id":"2003.01848","title":"On Emergent Communication in Competitive Multi-Agent Teams","created":"2020-03-04","cited_by_count":8},{"id":"1605.07133","title":"Towards Multi-Agent Communication-Based Language Learning","created":"2016-05-23","cited_by_count":7},{"id":"1911.01892","title":"Focus on What's Informative and Ignore What's not: Communication Strategies in a Referential Game","created":"2019-11-05","cited_by_count":7},{"id":"2007.12750","title":"Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data","created":"2020-07-24","cited_by_count":7},{"id":"2010.02975","title":"Supervised Seeded Iterated Learning for Interactive Language Learning","created":"2020-10-06","cited_by_count":7},{"id":"2210.11512","title":"Communication breakdown: On the low mutual intelligibility between human and neural captioning","created":"2022-10-20","cited_by_count":5},{"id":"1910.04872","title":"Modeling Conceptual Understanding in Image Reference Games","created":"2019-10-10","cited_by_count":4},{"id":"1911.04362","title":"To Populate is To Regulate","created":"2019-11-06","cited_by_count":4}],"next_cursor":"100"}