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
4
10
1
11
82
89
98
89
99
120
153
269
217
273
416
1,053
1,809
3,137
4,063
4,997
5,940
7,896
12,509
17,181
8,128
2000
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Papers (including subtopics)
Data Augmentation via Latent Diffusion for Saliency Prediction
ECCV 2024
Data-Augmented Curriculum Graph Neural Architecture Search under Distribution Shifts
AAAI 2024
Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models
ACL 2024
Data Contamination Calibration for Black-box LLMs
ACL 2024
Data, Data Everywhere: A Guide for Pretraining Dataset Construction
EMNLP 2024
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows
ACL 2024
Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls
JMLR 2024
Data-driven bifurcation analysis via learning of homeomorphism
L4DC 2024
Data-Driven Discovery of Design Specifications (Student Abstract)
AAAI 2024
Data-Driven Knowledge-Aware Inference of Private Information in Continuous Double Auctions
AAAI 2024
Data-driven strategy synthesis for stochastic systems with unknown nonlinear disturbances
L4DC 2024
Data driven verification of positive invariant sets for discrete, nonlinear systems
L4DC 2024
Data-efficient Large Vision Models through Sequential Autoregression
ICML 2024
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond
ICML 2024
Data Efficient Paradigms for Personalized Assessment of Black-Box Taskable AI Systems
AAAI 2024
Data Engineering for Scaling Language Models to 128K Context
ICML 2024
Data-faithful Feature Attribution: Mitigating Unobservable Confounders via Instrumental Variables
NeurIPS 2024
Data Filtering Networks
ICLR 2024
Data-flow Availability: Achieving Timing Assurance in Autonomous Systems
OSDI 2024
DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure
ACML 2024
Data Free Backdoor Attacks
NeurIPS 2024
Data-Free Hard-Label Robustness Stealing Attack
AAAI 2024
Data-Free Quantization via Pseudo-label Filtering
CVPR 2024
Data-mining and Extraction: the gold rush of AI on Indigenous Languages
EACL 2024
Data Mixture Inference Attack: BPE Tokenizers Reveal Training Data Compositions
NeurIPS 2024