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Core AI

68,645 papers (13 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Multimodal Learning (14,926) Large Language Models (9,515) Interpretability (8,292) Foundation Models (5,277) Agent Systems (4,710) Causal Inference (3,958) Multi-Agent Systems (3,842) AI Safety (3,602) Planning (3,482) Reasoning (3,360) Human-AI Interaction (2,465) Model Compression (2,258) Natural Language Processing (2,186) Responsible AI (2,130) Computer Vision (1,901) Game AI (1,846) Reinforcement Learning (1,698) Adversarial Learning (1,500) Autonomous Vehicles (1,488) Language (1,345) Fairness (1,279) Game Theory (1,129) Robotics (1,087) Dialogue Systems (1,066) Efficient Computing (956) Vision-Language Models (928) Knowledge Graph (735) Procedural Generation (709) Trajectory Prediction (676) Evaluation (655) Privacy (617) Natural Language Generation (573) Information Retrieval (541) Memory (526) Decision Making (480) Safety (474) Knowledge Representation (409) Knowledge (386) Information Extraction (378) Speech Processing (310) Knowledge Graphs (282) Security (256) Uncertainty Quantification (246) Representation Learning (239) Retrieval-Augmented Generation (225) Knowledge Editing (200) Question Answering (199) Attention (198) Robustness (186) Knowledge Distillation (185) Code Generation (168) Explainability (142) Brain-Computer Interface (141) Neural Networks (136) Anomaly Detection (132) Automated Reasoning (84) Natural Language Understanding (81) Multi-Lingual Learning (79) Education (64) Machine Translation (57) Learning Paradigms (57) Speech Recognition (55) Risk Management (51) Visual Question Answering (49) Communication (35) Motion Analysis (32) Natural Language Inference (29) Sentiment Analysis (19) Representation (17)

Papers per year

1
11
99
273
4,063
17,181
2000
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Papers (including subtopics)

Learning Bayesian networks with ancestral constraints NeurIPS 2016 Learning Compact Binary Descriptors With Unsupervised Deep Neural Networks CVPR 2016 Learning feed-forward one-shot learners NeurIPS 2016 Learning Granger Causality for Hawkes Processes ICML 2016 Learning Influence Functions from Incomplete Observations NeurIPS 2016 Learning in Games: Robustness of Fast Convergence NeurIPS 2016 Learning Latent Variable Models by Pairwise Cluster Comparison: Part II - Algorithm and Evaluation JMLR 2016 Learning Latent Variable Models by Pairwise Cluster Comparison: Part I - Theory and Overview JMLR 2016 Learning Multiagent Communication with Backpropagation NeurIPS 2016 Learning Online Smooth Predictors for Realtime Camera Planning Using Recurrent Decision Trees CVPR 2016 Learning Representations for Counterfactual Inference ICML 2016 Learning shape correspondence with anisotropic convolutional neural networks NeurIPS 2016 Learning Simple Algorithms from Examples ICML 2016 Learning Succinct Models: Pipelined Compression with L1-Regularization, Hashing, Elias-Fano Indices, and Quantization COLING 2016 Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods NeurIPS 2016 Learning to Communicate with Deep Multi-Agent Reinforcement Learning NeurIPS 2016 Learning to Filter with Predictive State Inference Machines ICML 2016 Learning to Generate with Memory ICML 2016 Learning to Localize Little Landmarks CVPR 2016 Learning to Poke by Poking: Experiential Learning of Intuitive Physics NeurIPS 2016 Learning Tree Structured Potential Games NeurIPS 2016 Learning under uncertainty: a comparison between R-W and Bayesian approach NeurIPS 2016 Learning values across many orders of magnitude NeurIPS 2016 Learning What and Where to Draw NeurIPS 2016 Lenient Learning in Independent-Learner Stochastic Cooperative Games JMLR 2016