本项目收集了各大顶会的最佳论文（自 2013 年起）。所有的数据都是手工输入的，所以 如果你发现有任何错误，欢迎开个 issue 提醒我。你也可以通过 创建 pull requests 的方式参与到这个项目中来。项目中的部分数据参考了 Jeff Huang 的网站，他收集了自 1996 年起计算机科学领域部分顶会的最佳论文，如果你感兴趣，也可以访问他的网站。
This repo collects best papers from various top conferences (since 2013). All the data are collected and entered by hand, so feel free to open an issue if you find anything wrong. You can also contribute to this repo by creating pull requests. Part of the data is collected by Jeff Huang. If you are interested in more best papers in computer science (since 1996), you can visit his website.
- Cross-domain
- Data Mining and Information Retrieval
- Computer Vision
- Natural Language Processing
This repo is writen in Markdown. Each entry follows the following format.
| Year | Paper |
| :-: | :- |
| 2020 | **[Paper title](Link to pdf)**<br>AuthorName (Organization); AuthorName (Organization) |When multiple best papers are available:
| Year | Paper |
| :-: | :- |
| 2020 | 1. **[Paper title](Link to pdf)**<br>AuthorName (Organization); AuthorName (Organization)<br>2. **[Paper title](Link to pdf)**<br>AuthorName (Organization); AuthorName (Organization) |The full list of AAAI outstanding papers (including best student papers and their Honorable Mentions) is presented on this website.
| Year | Paper |
|---|---|
| 2020 | WinoGrande: An Adversarial Winograd Schema Challenge at Scale Keisuke Sakaguchi (Allen Institute for Artificial Intelligence); Ronan Le Bras (Allen Institute for Artificial Intelligence); Chandra Bhagavatula (Allen Institute for Artificial Intelligence); Yejin Choi (University of Washington) |
| 2019 | How to Combine Tree-Search Methods in Reinforcement Learning Yonathan Efroni (Technion); Gal Dala (Technion); Bruno Scherrer (INRIA); Shie Mannor (Technion) |
| 2018 | Memory-Augmented Monte Carlo Tree Search Chenjun Xiao (University of Alberta); Jincheng Mei (University of Alberta); Martin Müller (University of Alberta) |
| 2017 | Label-Free Supervision of Neural Networks with Physics and Domain Knowledge Russell Stewart (Stanford University); Stefano Ermon (Stanford University) |
| 2016 | Bidirectional Search That Is Guaranteed to Meet in the Middle Robert C. Holte (University of Alberta); Ariel Felner (Ben-Gurion University); Guni Sharon (Ben-Gurion University); Nathan R. Sturtevant (University of Denver) |
| 2015 | From Non-Negative to General Operator Cost Partitioning Florian Pommerening (University of Basel); Malte Helmert (University of Basel); Gabriele Röger (University of Basel); Jendrik Seipp (University of Basel) |
| 2014 | Recovering from Selection Bias in Causal and Statistical Inference Elias Bareinboim (UCLA); Jin Tian (Iowa State University); Judea Pearl (UCLA) |
| 2013 | 1. HC-Search: Learning Heuristics and Cost Functions for Structured Prediction Janardhan Rao Doppa (Oregon State University); Alan Fern (Oregon State University); Prasad Tadepalli (Oregon State University) 2. SMILe: Shuffled Multiple-Instance Learning Gary Doran (Case Western Reserve University); Soumya Ray (Case Western Reserve University) |
IJCAI Distinguished papers.
| Year | Paper |
|---|---|
| 2019 | Boosting for Comparison-Based Learning Michaël Perrot (Max-Planck-Institute for Intelligent Systems); Ulrike von Luxburg (University of Tubingen) |
| 2018 | 1. Reasoning about Consensus when Opinions Diffuse through Majority Dynamics Vincenzo Auletta (University of Salerno); Diodato Ferraioli (University of Salerno); Gianluigi Greco (University of Calabria) 2. SentiGAN: Generating Sentimental Texts via Mixture Adversarial Networks Ke Wang (Peking University); Xiaojun Wan (Peking University) 3. From Conjunctive Queries to Instance Queries in Ontology-Mediated Querying Cristina Feier (University of Bremen); Carsten Lutz (University of Bremen); Frank Wolte (University of Liverpool) 4. What game are we playing? End-to-end learning in normal and extensive form games Chun Kai Ling (Carnegie Mellon University); Fei Fang (Carnegie Mellon University); J. Zico Kolter (Carnegie Mellon University) 5. Commonsense Knowledge Aware Conversation Generation with Graph Attention Hao Zhou (Tsinghua University); Tom Young (Beijing Institute of Technology); Minlie Huang (Tsinghua University); Haizhou Zhao, Sogou Inc.; Jingfang Xu, Sogou Inc.; Xiaoyan Zhu (Tsinghua University) 6. R-SVM+: Robust Learning with Privileged Information Xue Li (Wuhan University); Bo Du (Wuhan University); Chang Xu (University of Sydney); Yipeng Zhang (Wuhan University); Lefei Zhang (Wuhan University); Dacheng Tao (University of Sydney) 7. A Degeneracy Framework for Graph Similarity Giannis Nikolentzos, École Polytechnique; Polykarpos Meladianos (Athens University of Economics and Business); Stratis Limnios, École Polytechnique; Michalis Vazirgiannis (École Polytechnique) |
| 2017 | Foundations of Declarative Data Analysis Using Limit Datalog Programs Mark Kaminski (University of Oxford); Bernardo Cuenca Grau (University of Oxford); Egor V. Kostylev (University of Oxford); Boris Motik (University of Oxford); Ian Horrocks (University of Oxford) |
| 2016 | Hierarchical Finite State Controllers for Generalized Planning Javier Segovia (Universitat Pompeu Fabra); Sergio Jiménez (Universitat Pompeu Fabra); Anders Jonsson (Universitat Pompeu Fabra) |
| 2015 | 1. Bayesian Active Learning for Posterior Estimation Kirthevasan Kandasamy (Carnegie Mellon University); Jeff Schneider (Carnegie Mellon University); Barnabas Poczos (Carnegie Mellon University) 2. Recursive Decomposition for Nonconvex Optimization Abram L. Friesen (University of Washington); Pedro Domingos (University of Washington) |
| 2013 | 1. Bayesian Optimization in High Dimensions via Random Embeddings Ziyu Wang (University of British Columbia); Masrour Zoghi (University of Amsterdam); Frank Hutter (Freiberg University); David Matheson (University of British Columbia); Nando de Freitas (University of British Columbia) 2. Flexibility and Decoupling in the Simple Temporal Problem Michel Wilson (Delft University of Technology); Tomas Klos (Delft University of Technology); Cees Witteveen (Delft University of Technology); Bob Huisman (Delft University of Technology) |
| Year | Paper |
|---|---|
| 2019 | Distribution-Independent PAC Learning of Halfspaces with Massart Noise Ilias Diakonikolas (University of Wisconsin-Madison); Themis Gouleakis (Max Planck Institute for Informatics) |
| 2018 | 1. Non-delusional Q-learning and Value-iteration Tyler Lu; Dale Schuurmans; Craig Boutilier 2. Optimal Algorithms for Non-Smooth Distributed Optimization in Networks Kevin Scaman ; Francis Bach ; Sebastien Bubeck ; Laurent Massoulié ; Yin Tat Lee 3. Nearly Tight Sample Complexity Bounds for Learning Mixtures of Gaussians via Sample Compression Schemes Hassan Ashtiani ; Shai Ben-David ; Nick Harvey ; Christopher Liaw ; Abbas Mehrabian ; Yaniv Plan 4. Neural Ordinary Differential Equations Tian Qi Chen ; Yulia Rubanova ; Jesse Bettencourt ; David Duvenaud |
| 2017 | 1. Safe and Nested Subgame Solving for Imperfect-Information Games Noam Brown (Carnegie Mellon University); Tuomas Sandholm(Carnegie Mellon University) 2. Variance-based Regularization with Convex Objectives Hongseok Namkoong (Stanford University); John Duchi (Stanford University) 3. A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum (University College London), Wenkai Xu (University College London), Zoltan Szabo (École Polytechnique), Kenji Fukumizu (The Institute of Statistical Mathematics), Arthur Gretton (University College London) |
| 2016 | Value Iteration Networks Aviv Tamar (UC Berkeley); Yi Wu (UC Berkeley); Garrett Thomas (UC Berkeley); Sergey Levine (UC Berkeley); Pieter Abbeel (UC Berkeley) |
| 2015 | 1. Competitive Distribution Estimation: Why is Good-Turing Good Alon Orlitsky (UC San Diego); Ananda Suresh (UC San Diego) 2. Fast Convergence of Regularized Learning in Games Vasilis Syrgkanis (Microsoft Research); Alekh Agarwal (Microsoft Research); Haipeng Luo (Princeton University); Robert Schapire (Microsoft Research) |
| 2014 | 1. Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS) Anshumali Shrivastava (Cornell University); Ping Li (Rutgers University) 2. A* Sampling Christopher Maddison (University of Toronto); Daniel Tarlow (Microsoft Research); Tom Minka (Microsoft Research) |
| 2013 | 1. A memory frontier for complex synapses Subhaneil Lahiri (Stanford University); Surya Ganguli (Stanford University) 2. Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints Rishabh Iyer (University of Washington, Seattle); Jeff Bilmes (University of Washington, Seattle) 3. Scalable Influence Estimation in Continuous-Time Diffusion Networks Nan Du (Georgia Tech); Le Song (Georgia Tech); Manuel Gomez-Rodriguez (MPI for Intelligent Systems); Hongyuan Zha (Georgia Tech) |
ICML Outstanding Papers.
| Year | Paper |
|---|---|
| 2020 | 1. On Learning Sets of Symmetric Elements Haggai Maron (NVIDIA Research); Or Litany (Stanford University); Gal Chechik (Stanford University); Ethan Fetaya (Bar Ilan University) 2. Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems Kaixuan Wei (Beijing Institute of Technology); Angelica I Aviles-Rivero (University of Cambridge); Jingwei Liang (University of Cambridge); Ying Fu (Beijing Institute of Technology); Carola-Bibiane Schönlieb (University of Cambridge); Hua Huang (Beijing Institute of Technology) |
| 2019 | 1. Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello (ETH Zurich); Stefan Bauer (MaxPlanck Institute for Intelligent Systems); Mario Lucic (Google Brain); Gunnar Rätsch (Google Brain); Sylvain Gelly (ETH Zurich); Bernhard Schölkopf (MaxPlanck Institute for Intelligent Systems); Olivier Bachem (Google Brain) 2. Rates of Convergence for Sparse Variational Gaussian Process Regression David R. Burt (University of Cambridge); Carl Edward Rasmussen (University of Cambridge); Mark van der Wilk (PROWLER.io) |
| 2018 | 1. Delayed Impact of Fair Machine Learning Lydia T. Liu (University of California Berkeley); Sarah Dean (University of California Berkeley); Esther Rolf (University of California Berkeley); Max Simchowitz (University of California Berkeley); Moritz Hardt (University of California Berkeley) 2. Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye (Massachusetts Institute of Technology); Nicholas Carlini (University of California Berkeley); David Wagner (University of California Berkeley) |
| 2017 | Understanding Black-box Predictions via Influence Functions Pang Wei Koh (Stanford University); Percy Liang (Stanford University) |
| 2016 | 1. Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling Christopher De Sa (Stanford University); Chris Re (Stanford University); Kunle Olukotun (Stanford University) 2. Pixel Recurrent Neural Networks Aaron Van den Oord (Google); Nal Kalchbrenner (Google); Koray Kavukcuoglu (Google) 3. Dueling Network Architectures for Deep Reinforcement Learning Ziyu Wang (Google); Tom Schaul (Google); Matteo Hessel (Google); Hado van Hasselt (Google); Marc Lanctot (Google); Nando de Freitas (University of Oxford) |
| 2015 | 1. A Nearly-Linear Time Framework for Graph-Structured Sparsity Chinmay Hegde (Massachusetts Institute of Technology); Piotr Indyk (Massachusetts Institute of Technology); Ludwig Schmid (Massachusetts Institute of Technology) 2. Optimal and Adaptive Algorithms for Online Boosting Alina Beygelzimer (Yahoo! Research); Satyen Kale (Yahoo! Research); Haipeng Luo (Princeton University) |
| 2014 | Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis Jian Tang (Peking University); Zhaoshi Meng (University of Michigan); XuanLong Nguyen (University of Michigan); Qiaozhu Mei (University of Michigan); Ming Zhang (Peking University) |
| 2013 | 1. Vanishing Component Analysis Roi Livni (The Hebrew University of Jerusalum); David Lehavi (Hewlett-Packard Labs); Sagi Schein (Hewlett-Packard Labs); Hila Nachlieli (Hewlett-Packard Labs); Shai Shalev Shwartz (The Hebrew University of Jerusalum); Amir Globerson (The Hebrew University of Jerusalum) 2. Fast Semidifferential-based Submodular Function Optimization Rishabh Iyer (University of Washington); Stefanie Jegelka (University of California Berkeley); Jeff Bilmes (University of Washington) |
| Year | Paper |
|---|---|
| 2020 | Open Intent Extraction from Natural Language Interactions Nikhita Vedula (The Ohio State University); Nedim Lipka (Adobe); Pranav Maneriker (The Ohio State University); Srinivasan Parthasarathy (The Ohio State University) |
| 2019 | 1. Ermes: Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification Zhenpeng Chen (Peking University); Sheng Shen (University of California, Berkeley); Ziniu Hu (University of California, Berkeley); Xuan Lu (Peking University); Qiaozhu Mei (University of Michigan); Xuanzhe Liu (Peking University) 2. OUTGUARD: Detecting In-Browser Covert Cryptocurrency Mining in the Wild Amin Kharraz (University of Illinois at Urbana-Champaign); Zane Ma (University of Illinois at Urbana-Champaign); Paul Murley (University of Illinois at Urbana-Champaign); Charles Lever (Georgia Institute of Technology); Joshua Mason (University of Illinois at Urbana-Champaign); Andrew Miller (University of Illinois at Urbana-Champaign); Nikita Borisov (University of Illinois at Urbana-Champaign); Manos Antonakakis (Georgia Institute of Technology); Michael Bailey (University of Illinois at Urbana-Champaign) |
| 2018 | HighLife: Higher-arity Fact Harvesting Patrick Ernst (Saarland Informatics Campus in Saarbrücken); Amy Siu (Saarland Informatics Campus in Saarbrücken); Gerhard Weikum (Saarland Informatics Campus in Saarbrücken) |
| 2017 | Currently missing. |
| 2016 | Social Networks Under Stress Daniel Romero (University of Michigan); Brian Uzzi (Northwestern University); Jon Kleinberg (Cornell University) |
| 2015 | HypTrails: A Bayesian Approach for Comparing Hypotheses About Human Trails on the Web Philipp Singer (GESIS - Leibniz Institute for the Social Sciences); Denis Helic (Graz University of Technology); Andreas Hotho, University of Würzburg; Markus Strohmaier (GESIS - Leibniz Institute for the Social Sciences） |
| 2014 | Efficient Estimation for High Similarities using Odd Sketches Michael Mitzenmacher (Harvard University); Rasmus Pagh (IT University of Copenhagen); Ninh Pham (IT University of Copenhagen) |
| 2013 | No Country for Old Members: User Lifecycle and Linguistic Change in Online Communities Cristian Danescu-Niculescu-Mizil (Stanford University); Robert West (Stanford University); Dan Jurafsky (Stanford University); Jure Leskovec (Stanford University); Christopher Potts (Stanford University) |
KDD has two paper tracks, i.e., the Research Track and the Applied Data Science Track. I only report the best papers for the research track in this repo but the ADS track is remarkable as well.
| Year | Paper |
|---|---|
| 2020 | On Sampled Metrics for Item Recommendation Walid Krichene (Google Research); Steffen Rendle (Google Research) |
| 2019 | Network Density of States Kun Dong (Cornell University); Austin Benson (Cornell University); David Bindel (Cornell University) |
| 2018 | Adversarial Attacks on Neural Networks for Graph Data Daniel Zügner (Technical University of Munich); Amir Akbarnejad (Technical University of Munich); Stephan Günnemann (Technical University of Munich) |
| 2017 | Accelerating Innovation Through Analogy Mining Tom Hope (Hebrew University of Jerusalem); Joel Chan (Carnegie Mellon University); Aniket Kittur (Carnegie Mellon University); Dafna Shahaf (Hebrew University of Jerusalem) |
| 2016 | FRAUDAR: Bounding Graph Fraud in the Face of Camouflage Bryan Hooi (Carnegie Mellon University); Hyun Ah Song (Carnegie Mellon University); Alex Beutel (Carnegie Mellon University); Neil Shah (Carnegie Mellon University); Kijung Shin (Carnegie Mellon University); Christos Faloutsos (Carnegie Mellon University) |
| 2015 | Efficient Algorithms for Public-Private Social Networks Flavio Chierichetti (Sapienza University of Rome); Alessandro Epasto (Brown University); Ravi Kumar (Google); Silvio Lattanzi (Google); Vahab Mirrokni (Google) |
| 2014 | Reducing the Sampling Complexity of Topic Models Aaron Li (Carnegie Mellon University); Amr Ahmed (Google); Sujith Ravi (Google); Alexander Smola (Carnegie Mellon University) |
| 2013 | Simple and Deterministic Matrix Sketching Edo Liberty (Yahoo! Research) |
The full list of SIGIR best papers is presented on this website.
| Year | Paper |
|---|---|
| 2020 | Controlling Fairness and Bias in Dynamic Learning-to-Rank Marco Morik (Technische Univerität Berlin); Ashudeep Singh (Cornell University); Jessica Hong (Cornell University); Thorsten Joachims (Cornell University) |
| 2019 | Variance Reduction in Gradient Exploration for Online Learning to Rank Huazheng Wang (University of Virginia); Sonwoo Kim (University of Virginia); Eric McCord-Snook (University of Virginia); Qingyun Wu (University of Virginia); Hongning Wang (University of Virginia) |
| 2018 | Should I Follow the Crowd? A Probabilistic Analysis of the Effectiveness of Popularity in Recommender Systems Rocío Cañamares (Universidad Autónoma de Madrid); Pablo Castells (Universidad Autónoma de Madrid) |
| 2017 | BitFunnel: Revisiting Signatures for Search Bob Goodwin (Microsoft); Michael Hopcroft (Microsoft); Dan Luu (Microsoft); Alex Clemmer (Heptio); Mihaela Curmei (Microsoft); Sameh Elnikety (Microsoft); Yuxiong He (Microsoft) |
| 2016 | Understanding Information Need: An fMRI Study Yashar Moshfeghi (University of Glasgow); Peter Triantafillou (University of Glasgow); Frank E. Pollick (University of Glasgow) |
| 2015 | QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees Claudio Lucchese (Istituto di Scienza e Tecnologie dell'Informazione); Franco Maria Nardini (Istituto di Scienza e Tecnologie dell'Informazione); Salvatore Orlando, Università di Venezia; Raffaele Perego (Istituto di Scienza e Tecnologie dell'Informazione); Nicola Tonellotto (Istituto di Scienza e Tecnologie dell'Informazione); Rossano Venturini (Istituto di Scienza e Tecnologie dell'Informazione) |
| 2014 | Partitioned Elias-Fano Indexes Giuseppe Ottaviano (Istituto di Scienza e Tecnologie dell'Informazione); Rossano Venturini (Università di Pisa) |
| 2013 | Beliefs and Biases in Web Search Ryen W. White (Microsoft Research) |
| Year | Paper |
|---|---|
| 2019 | AutoGRD: Model Recommendation Through Graphical Dataset Representation Noy Cohen-Shapira (Ben Gurion University of the Negev); Lior Rokach (Ben Gurion University of the Negev); Bracha Shapira (Ben Gurion University of the Negev); Gilad Katz (Ben Gurion University of the Negev); Roman Vainshtein (Ben Gurion University of the Negev) |
| 2018 | Relevance estimation with multiple information sources on search engine result pages Junqi Zhang (Tsinghua University); Yiqun Liu (Tsinghua University); Shaoping Ma (Tsinghua University); Qi Tian (University of Texas at San Antonio) |
| 2017 | Hike: A Hybrid Human-Machine Method for Entity Alignment in Large-Scale Knowledge Bases Yan Zhuang (Tsinghua University); Guoliang Li (Tsinghua University); Zhuojian Zhong (Tsinghua University); Jianhua Feng (Tsinghua University) |
| 2016 | Vandalism Detection in Wikidata Stefan Heindorf (Paderborn University); Martin Potthast (Bauhaus-Universität Weimar); Benno Stein (Bauhaus-Universität Weimar); Gregor Engels (Paderborn University) |
| 2015 | Assessing the Impact of Syntactic and Semantic Structures for Answer Passages Reranking Kateryna Tymoshenko (University of Trento); Alessandro Moschitti (Qatar Computing Research Institute) |
| 2014 | Cross-Device Search George Montanez (Carnegie Mellon University); Ryen White (Microsoft Research); Xiao Huang (Microsoft) |
| 2013 | Penguins in Sweaters, or Serendipitous Entity Search on User-generated Content Ilaria Bordino (Yahoo! Research); Yelena Mejova (Yahoo! Research); Mounia Lalmas (Yahoo! Research) |
| Year | Paper |
|---|---|
| 2020 | Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild Shangzhe Wu (University of Oxford); Christian Rupprecht (University of Oxford); Andrea Vedaldi (Oxford University) |
| 2019 | A theory of Fermat Paths for Non-Line-of-Sight Shape Reconstruction Shumian Xin (Carnegie Mellon University); Sotiris Nousias (University of Toronto); Kiriakos N. Kutulakos (University of Toronto); Aswin C. Sankaranarayanan (Carnegie Mellon University); Srinivasa G. Narasimhan (Carnegie Mellon University); Ioannis Gkioulekas (Carnegie Mellon University) |
| 2018 | Taskonomy: Disentangling Task Transfer Learning Amir R. Zamir (Stanford University); Alexander Sax (Stanford University); William Shen (Stanford University); Leonidas Guibas (Stanford University); Jitendra Malik (University of California Berkeley); Silvio Savarese (Stanford University) |
| 2017 | 1. Densely Connected Convolutional Networks Zhuang Liu (Tsinghua University); Gao Huang (Cornell University); Laurens van der Maaten (Facebook AI Research); Kilian Q. Weinberger (Cornell University) 2. Learning from Simulated and Unsupervised Images through Adversarial Training Ashish Shrivastava (Apple Inc.); Tomas Pfister (Apple Inc.); Oncel Tuzel (Apple Inc.); Josh Susskind (Apple Inc.); Wenda Wang (Apple Inc.); Russ Webb (Apple Inc.) |
| 2016 | Deep Residual Learning for Image Recognition Kaiming He (Microsoft Research); Xiangyu Zhang (Microsoft Research); Shaoqing Ren (Microsoft Research); Jian Sun (Microsoft Research) |
| 2015 | DynamicFusion: Reconstruction and Tracking of Non-rigid Scenes in Real-Time Richard A. Newcombe (University of Washington); Dieter Fox (University of Washington); Steven M. Seitz (University of Washington) |
| 2014 | What Camera Motion Reveals About Shape with Unknown BRDF Manmohan Chandraker (NEC Labs America) |
| 2013 | Fast, Accurate Detection of 100,000 Object Classes on a Single Machine Thomas Dean (Google); Mark A. Ruzon (Google); Mark Segal (Google); Jonathon Shlens (Google); Sudheendra Vijayanarasimhan (Google); Jay Yagnik (Google) |
The ICCV Best Paper Award is also called the Marr Prize, named after British neuroscientist David Marr.
| Year | Paper |
|---|---|
| 2019 | SinGAN: Learning a Generative Model from a Single Natural Image Tamar Rott Shaham (Israel Institute of Technology); Tomer Michaeli (Israel Institute of Technology); Tali Dekel (Google Research) |
| 2017 | Mask R-CNN Kaiming He (Facebook AI Research); Georgia Gkioxari (Facebook AI Research); Piotr Dollar (Facebook AI Research); Ross Girshick (Facebook AI Research) |
| 2015 | Deep Neural Decision Forests Peter Kontschieder (Microsoft Research); Madalina Fiterau (Carnegie Mellon University); Antonio Criminisi (Microsoft Research); Samuel Rota Bulò (Microsoft Research) |
| 2013 | From Large Scale Image Categorization to Entry-Level Categories Vicente Ordonez (University of North Carolina at Chapel Hill); Jia Deng (Stanford University); Yejin Choi (Stony Brook University); Alexander Berg (University of North Carolina at Chapel Hill); Tamara Berg (University of North Carolina at Chapel Hill) |
| Year | Paper |
|---|---|
| 2020 | Beyond Accuracy: Behavioral Testing of NLP Models with CheckList Marco Tulio Ribeiro (Microsoft Research), Tongshuang Wu (University of Washington), Carlos Guestrin (University of Washington), Sameer Singh (University of Washington) |
| 2019 | Bridging the Gap between Training and Inference for Neural Machine Translation Wen Zhang (University of Chinese Academy of Sciences); Yang Feng (University of Chinese Academy of Sciences); Fandong Meng (WeChat AI); Di You (Worcester Polytechnic Institute); Qun Liu (Huawei Noah’s Ark Lab) |
| 2018 | Finding syntax in human encephalography with beam search John Hale (Cornell University); Chris Dyer (DeepMind); Adhiguna Kuncoro (University of Oxford); Jonathan R. Brennan (University of Michigan) |
| 2017 | Probabilistic Typology: Deep Generative Models of Vowel Inventories Ryan Cotterell (Johns Hopkins University); Jason Eisner (Johns Hopkins University) |
| 2016 | Finding Non-Arbitrary Form-Meaning Systematicity Using String-Metric Learning for Kernel Regression E. Darío Gutiérrez (University of California Berkeley); Roger Levy (Massachusetts Institute of Technology); Benjamin K. Bergen (University of California San Diego) |
| 2015 | 1. Improving Evaluation of Machine Translation Quality Estimation Yvette Graham (Trinity College Dublin) 2. Learning Dynamic Feature Selection for Fast Sequential Prediction Emma Strubell (University of Massachusetts Amherst); Luke Vilnis (University of Massachusetts Amherst); Kate Silverstein (University of Massachusetts Amherst); Andrew McCallum (University of Massachusetts Amherst) |
| 2014 | Fast and Robust Neural Network Joint Models for Statistical Machine Translation Jacob Devlin (Raytheon BBN Technologies); Rabih Zbib (Raytheon BBN Technologies); Zhongqiang Huang (Raytheon BBN Technologies); Thomas Lamar (Raytheon BBN Technologies); Richard Schwartz (Raytheon BBN Technologies); John Makhoul (Raytheon BBN Technologies) |
| 2013 | Grounded Language Learning from Video Described with Sentences Haonan Yu (Purdue University); Jeffrey Mark Siskind (Purdue University) |