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Core Methods

51,083 papers (8 classified directly here)

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

Representation Learning (22,308) Classification (15,497) Regression (5,281) Clustering (3,809) Embedding Learning (3,795) Metric Learning (2,938) Graph Neural Networks (1,211) Graphical Models (1,093) Feature Learning (891) Kernel Methods (795) Dimensionality Reduction (780) Interpretability (512) Feature Selection (511) Matrix Factorization (408) Ranking (315) Ensemble Methods (300) Support Vector Machine (295) Anomaly Detection (281) Sequence Modeling (244) Structured Prediction (237) Sequence Labeling (157) Topic Modeling (150) Sparse Coding (140) Matrix Completion (131) Neural Networks (114) Retrieval (105) Density Estimation (104) Estimation (83) Inference (56) Decision Tree (50) Feature Extraction (40) Model Selection (39) Prediction (35) Information Extraction (7)

Papers per year

4
51
357
966
4,853
5,823
2000
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Papers (including subtopics)

Beyond Accuracy: Alignment and Error Detection across Languages in the Bi-GSM8K Math-Teaching Benchmark EACL 2026 Beyond Coherence: Improving Temporal Consistency and Interpretability in Dynamic Topic Models EACL 2026 Beyond Content: A Comprehensive Speech Toxicity Dataset and Detection Framework Incorporating Paralinguistic Cues AAAI 2026 Beyond Cosine Similarity: Magnitude-Aware CLIP for No-Reference Image Quality Assessment AAAI 2026 Beyond Faces: A Multimodal Person Clustering for Unconstrained Environments WACV 2026 Beyond Fixed Depth: Adaptive Graph Neural Networks for Node Classification Under Varying Homophily AAAI 2026 Beyond Local Patterns: Multiscale Inconsistency Learning for Graph Anomaly Detection AAAI 2026 Beyond Missing Data Imputation: Information-Theoretic Coupling of Missingness and Class Imbalance for Optimal Irregular Time Series Classification AAAI 2026 Beyond MSE: Ordinal Cross-Entropy for Probabilistic Time Series Forecasting AAAI 2026 Beyond Neuron-Level Sparsity: Achieving Faithful and Interpretable LLMs with Mixture of Decoders AAAI 2026 Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions AAAI 2026 Beyond Observations: Reconstruction Error-Guided Irregularly Sampled Time Series Representation Learning AAAI 2026 Beyond Real Weights: Hypercomplex Representations for Stable Quantization WACV 2026 Beyond Sampling: Self-Sorting for Long-Context Ranking EACL 2026 Beyond Semantics: How Temporal Biases Shapes Retrieval in Transformer and State-Space Models EACL 2026 Beyond the Encoder: Joint Encoder-Decoder Contrastive Pre-Training Improves Dense Prediction WACV 2026 Beyond Tokens: Concept-Level Training Objectives for LLMs EACL 2026 Beyond Tokens: Dynamic Latent Reasoning via Semantic Residual Refinement AAAI 2026 Biasless Language Models Learn Unnaturally: How LLMs Fail to Distinguish the Possible from the Impossible EACL 2026 BiCA: Effective Biomedical Dense Retrieval with Citation-Aware Hard Negatives AAAI 2026 Bid Farewell to Seesaw: Towards Accurate Long-Tail Session-Based Recommendation via Dual Constraints of Hybrid Intents AAAI 2026 BidMatch: Boosting Semi-Supervised Learning by Bi-Dimensional Sample Weight Guidance AAAI 2026 BiHiTo: Biomolecular Hierarchy-inspired Tokenization AAAI 2026 Bi-ICE: An Inner Interpretable Framework for Image Classification via Bi-directional Interactions between Concept and Input Embeddings WACV 2026 Bi-Level Contextual Bandits for Individualized Resource Allocation Under Delayed Feedback AAAI 2026