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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)

Weight Entropy-Maximised Evidential Metamodel for Uncertainty Quantification (Student Abstract) AAAI 2026 Weight Space Correlation Analysis: Quantifying Feature Utilization in Deep Learning Models MIDL 2026 Weight Space Representation Learning via Neural Field Adaptation CVPR 2026 Well Begun, Half Done: Reinforcement Learning with Prefix Optimization for LLM Reasoning AAAI 2026 What About the Scene With the Hitler Reference? HAUNT: A Framework to Probe LLMs’ Self-consistency in Closed Domains Via Adversarial Nudge ACL 2026 What Are They Filtering Out? An Experimental Benchmark of Filtering Strategies for Harm Reduction in Pretraining Datasets AAAI 2026 What Brain Data Adds to Language Model Training CoNLL 2026 What Capable Agents Must Know: Selection Theorems for Robust Decision-Making under Uncertainty UAI 2026 What Deserves Memory: Adaptive Memory Distillation for LLM Agents ACL 2026 What Do LLMs Learn First? Asymmetric Learning Dynamics of Input Complexity and Output Ambiguity in Preference Alignment ACL 2026 What Do Visual Tokens Really Encode? Uncovering Sparsity and Redundancy in Multimodal Large Language Models CVPR 2026 What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap Dependencies CoNLL 2026 What Happens When: Learning Temporal Orders of Events in Videos WACV 2026 What If Consensus Lies? Selective-Complementary Reinforcement Learning at Test Time ACL 2026 What is a protest anyway? Codebook conceptualization is still a first-order concern in LLM-era classification ACL 2026 What Is the Optimal Ranking Score Between Precision and Recall? We Can Always Find It and It Is Rarely F1 CVPR 2026 What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning ACL 2026 What Makes a Good Generated Image? Investigating Human and Multimodal LLM Image Preference Alignment AAAI 2026 What Makes a Good Query? Measuring the Impact of Human-Confusing Linguistic Features on LLM Performance EACL 2026 What Makes a Good Speech Tokenizer for LLM-Centric Speech Generation? A Systematic Study AAAI 2026 What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations ACL 2026 What Makes Good Instruction-Tuning Data? An In-Context Learning Perspective ACL 2026 What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context ACL 2026 What Matters to an LLM? Behavioral and Computational Evidences from Summarization EACL 2026 What Moves the Pareto Frontier in Tool-Using Agents? A Compute-Aware Study of ReAct Variants ACL 2026