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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)

Topologically Faithful Image Segmentation via Induced Matching of Persistence Barcodes ICML 2023 ToThePoint: Efficient Contrastive Learning of 3D Point Clouds via Recycling CVPR 2023 TOT:Topology-Aware Optimal Transport for Multimodal Hate Detection AAAI 2023 ToViLaG: Your Visual-Language Generative Model is Also An Evildoer EMNLP 2023 Toward Adversarial Training on Contextualized Language Representation ICLR 2023 Toward Re-Identifying Any Animal NeurIPS 2023 Towards a better understanding of representation dynamics under TD-learning ICML 2023 Towards Adaptive Prefix Tuning for Parameter-Efficient Language Model Fine-tuning ACL 2023 Towards a Deep Understanding of Multilingual End-to-End Speech Translation EMNLP 2023 Towards a Holistic Understanding of Mathematical Questions with Contrastive Pre-training AAAI 2023 Towards Alleviating the Object Bias in Prompt Tuning-based Factual Knowledge Extraction ACL 2023 Towards a Mechanistic Interpretation of Multi-Step Reasoning Capabilities of Language Models EMNLP 2023 Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompts EMNLP 2023 Towards Artistic Image Aesthetics Assessment: A Large-Scale Dataset and a New Method CVPR 2023 Towards a Smaller Student: Capacity Dynamic Distillation for Efficient Image Retrieval CVPR 2023 Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering ICML 2023 Towards Better Hierarchical Text Classification with Data Generation ACL 2023 Towards Better Representations for Multi-Label Text Classification with Multi-granularity Information EMNLP 2023 Towards Bridging the Performance Gaps of Joint Energy-Based Models CVPR 2023 Towards Building More Robust NER datasets: An Empirical Study on NER Dataset Bias from a Dataset Difficulty View EMNLP 2023 Towards Domain Generalization for Multi-View 3D Object Detection in Bird-Eye-View CVPR 2023 Towards Effective Instance Discrimination Contrastive Loss for Unsupervised Domain Adaptation ICCV 2023 Towards Efficient Use of Multi-Scale Features in Transformer-Based Object Detectors CVPR 2023 Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly NeurIPS 2023 Towards Example-Based NMT with Multi-Levenshtein Transformers EMNLP 2023