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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 Influence-Receptivity Network Structure with Guarantee AISTATS 2019 Learning in Generalized Linear Contextual Bandits with Stochastic Delays NeurIPS 2019 Learning in Non-convex Games with an Optimization Oracle COLT 2019 Learning Interpretable Negation Rules via Weak Supervision at Document Level: A Reinforcement Learning Approach NAACL 2019 Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields IJCAI 2019 Learning-In-The-Loop Optimization: End-To-End Control And Co-Design Of Soft Robots Through Learned Deep Latent Representations NeurIPS 2019 Learning Latent Dynamics for Planning from Pixels ICML 2019 Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds EMNLP 2019 Learning Lightweight Lane Detection CNNs by Self Attention Distillation ICCV 2019 Learning Linear-Quadratic Regulators Efficiently with only √T Regret ICML 2019 Learning Low-precision Neural Networks without Straight-Through Estimator (STE) IJCAI 2019 Learning Mean-Field Games NeurIPS 2019 Learning Mixed-Curvature Representations in Product Spaces ICLR 2019 Learning Models from Data with Measurement Error: Tackling Underreporting ICML 2019 Learning Models of Sequential Decision-Making with Partial Specification of Agent Behavior AAAI 2019 Learning Monocular Depth Estimation Infusing Traditional Stereo Knowledge CVPR 2019 Learning Multimodal Graph-to-Graph Translation for Molecule Optimization ICLR 2019 Learning Natural Language Interfaces with Neural Models Interspeech 2019 Learning Neural PDE Solvers with Convergence Guarantees ICLR 2019 Learning Neurosymbolic Generative Models via Program Synthesis ICML 2019 Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making AAAI 2019 Learning Optimal Strategies to Commit To AAAI 2019 Learning Options with Interest Functions AAAI 2019 Learning Parametric Constraints in High Dimensions from Demonstrations CoRL 2019 Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids ICLR 2019