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Learning Types

32,670 papers (1 classified directly here)

Representation Learning (5,307) Multimodal Learning (3,969) Self-Supervised Learning (3,492) Transfer Learning (2,890) Adversarial Learning (2,199) Deep Learning (1,883) Contrastive Learning (1,730) Reinforcement Learning (1,500) Knowledge Distillation (1,494) Fine-Tuning (1,117) Multi-Task Learning (1,069) Domain Adaptation (977) Zero-Shot Learning (758) Unsupervised Learning (734) Few-Shot Learning (694) Classification (621) Retrieval-Augmented Generation (606) Data Augmentation (583) Semi-Supervised Learning (450) Weakly Supervised Learning (429) Continual Learning (408) In-Context Learning (387) Sequence Modeling (375) Meta-Learning (252) Metric Learning (232) Ensemble Learning (223) Federated Learning (215) Multi-Lingual Learning (199) Robustness (197) Parameter-Efficient Fine-Tuning (190) Imitation Learning (180) Prompt Engineering (170) Chain-of-Thought Reasoning (153) Curriculum Learning (146) Synthetic Data Generation (143) Reinforcement Learning from Human Feedback (141) Multi-Label Classification (123) Regression (117) Generative Model (109) Semantic Segmentation (106) Domain Generalization (105) Uncertainty Quantification (98) Controllable Generation (93) Text Generation (86) Neural Architecture Search (80) Object Detection (80) Image Generation (79) Multi-Agent Systems (76) Feature Learning (74) Preference Learning (73) Machine Translation (71) Out-of-Distribution Detection (68) Machine Unlearning (63) Generation (61) Reasoning (54) Multi-View Learning (53) Time Series (52) Instruction Tuning (50) Distributed Learning (50) Image Restoration (49) Chain-of-Thought (48) Active Learning (47) Text Classification (43) Distribution Shift (43) Structured Prediction (42) Clustering (41) Image Classification (40) Model Merging (37) Sparse Learning (36) Sequence Labeling (36) Multi-Instance Learning (35) Anomaly Detection (33) Image Processing (33) Code Generation (31) Fairness (30) Robust Learning (28) Multi-Domain Learning (27) Supervised Learning (26) Model-Based RL (25) Natural Language Generation (24) Privacy (21) Multi-Objective Optimization (19) Multi-Scale Learning (19) Neural Machine Translation (18) Causal Inference (14) Instance Segmentation (9) Interactive Learning (9) Multi-Label Learning (9) Multi-Source Learning (9) Multi-Class Classification (8)
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Papers (including subtopics)

InterpBench: Semi-Synthetic Transformers for Evaluating Mechanistic Interpretability Techniques NeurIPS 2024 Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding CVPR 2024 Interpretable Mesomorphic Networks for Tabular Data NeurIPS 2024 InterpretARA: Enhancing Hybrid Automatic Readability Assessment with Linguistic Feature Interpreter and Contrastive Learning AAAI 2024 Interpreting and Analysing CLIP's Zero-Shot Image Classification via Mutual Knowledge NeurIPS 2024 Interpreting Conversational Dense Retrieval by Rewriting-Enhanced Inversion of Session Embedding ACL 2024 INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning ACL 2024 INTERVENOR: Prompting the Coding Ability of Large Language Models with the Interactive Chain of Repair ACL 2024 Interventional Speech Noise Injection for ASR Generalizable Spoken Language Understanding EMNLP 2024 Inter-X: Towards Versatile Human-Human Interaction Analysis CVPR 2024 Into the Unknown: Generating Geospatial Descriptions for New Environments ACL 2024 IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors NeurIPS 2024 Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models CVPR 2024 Intrinsic Phase-Preserving Networks for Depth Super Resolution AAAI 2024 Intrinsic Self-Supervision for Data Quality Audits NeurIPS 2024 Introducing GenCeption for Multimodal LLM Benchmarking: You May Bypass Annotations NAACL 2024 Introducing Routing Functions to Vision-Language Parameter-Efficient Fine-Tuning with Low-Rank Bottlenecks ECCV 2024 Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level NeurIPS 2024 Invariant Risk Minimization Is A Total Variation Model ICML 2024 Inverse Factorized Soft Q-Learning for Cooperative Multi-agent Imitation Learning NeurIPS 2024 Inverse-Q*: Token Level Reinforcement Learning for Aligning Large Language Models Without Preference Data EMNLP 2024 Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps NeurIPS 2024 Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) Models EMNLP 2024 Investigating Large Language Models for Complex Word Identification in Multilingual and Multidomain Setups EMNLP 2024 Investigating Multilingual Instruction-Tuning: Do Polyglot Models Demand for Multilingual Instructions? EMNLP 2024