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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)

LaRA: Large Rank Adaptation for Speech and Text Cross-Modal Learning in Large Language Models EMNLP 2024 Large Language Model for Multi-Domain Translation: Benchmarking and Domain CoT Fine-tuning EMNLP 2024 Large Language Models Are Challenged by Habitat-Centered Reasoning EMNLP 2024 Large Language Models Are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales AAAI 2024 Large Language Models are Few-Shot Training Example Generators: A Case Study in Fallacy Recognition ACL 2024 Large Language Models are In-context Teachers for Knowledge Reasoning EMNLP 2024 Large Language Models Are Involuntary Truth-Tellers: Exploiting Fallacy Failure for Jailbreak Attacks EMNLP 2024 Large Language Models as Optimizers ICLR 2024 Large Language Models Can Be Contextual Privacy Protection Learners EMNLP 2024 Large Language Models can Share Images, Too! ACL 2024 Large Language Models for Propaganda Span Annotation EMNLP 2024 Large Language Models for Time Series: A Survey IJCAI 2024 Large Language Models Know What is Key Visual Entity: An LLM-assisted Multimodal Retrieval for VQA EMNLP 2024 Large Language Models Must Be Taught to Know What They Don’t Know NeurIPS 2024 Large Language Models Relearn Removed Concepts ACL 2024 Large Occluded Human Image Completion via Image-Prior Cooperating AAAI 2024 Large Vision-Language Models as Emotion Recognizers in Context Awareness ACML 2024 LaSCal: Label-Shift Calibration without target labels NeurIPS 2024 LaSe-E2V: Towards Language-guided Semantic-aware Event-to-Video Reconstruction NeurIPS 2024 LASIL: Learner-Aware Supervised Imitation Learning For Long-term Microscopic Traffic Simulation CVPR 2024 Latent Concept-based Explanation of NLP Models EMNLP 2024 LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration WACV 2024 Latent Functional Maps: a spectral framework for representation alignment NeurIPS 2024 Latent Learningscape Guided In-context Learning ACL 2024 Latent Representation Entropy Density for Distribution Shift Detection UAI 2024