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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)

TraceEvader: Making DeepFakes More Untraceable via Evading the Forgery Model Attribution AAAI 2024 Trace-of-Thought Prompting: Investigating Prompt-Based Knowledge Distillation Through Question Decomposition ACL 2024 Tracking linguistic information in transformer-based sentence embeddings through targeted sparsification ACL 2024 Trade-Offs in Fine-Tuned Diffusion Models between Accuracy and Interpretability AAAI 2024 Train-Attention: Meta-Learning Where to Focus in Continual Knowledge Learning NeurIPS 2024 Training and Fine-Tuning NMT Models for Low-Resource Languages Using Apertium-Based Synthetic Corpora EMNLP 2024 Training Data Attribution via Approximate Unrolling NeurIPS 2024 Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning CVPR 2024 Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality (extended abstract) COLT 2024 Training-free Deep Concept Injection Enables Language Models for Video Question Answering EMNLP 2024 Training-Free Object Counting With Prompts WACV 2024 Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts CVPR 2024 Training Graph Transformers via Curriculum-Enhanced Attention Distillation ICLR 2024 Training Implicit Generative Models via an Invariant Statistical Loss AISTATS 2024 Training Language Models to Generate Text with Citations via Fine-grained Rewards ACL 2024 Train Once, Use Flexibly: A Modular Framework for Multi-Aspect Neural News Recommendation EMNLP 2024 TrajCLIP: Pedestrian trajectory prediction method using contrastive learning and idempotent networks NeurIPS 2024 Transcendence: Generative Models Can Outperform The Experts That Train Them NeurIPS 2024 Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detection CVPR 2024 Transcoders find interpretable LLM feature circuits NeurIPS 2024 Transcriptomics-guided Slide Representation Learning in Computational Pathology CVPR 2024 TransFace: Unit-Based Audio-Visual Speech Synthesizer for Talking Head Translation ACL 2024 Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and Flatness NeurIPS 2024 Transferable Adversarial Attacks for Object Detection Using Object-Aware Significant Feature Distortion AAAI 2024 Transferable Adversarial Attacks on SAM and Its Downstream Models NeurIPS 2024