Learning Types
56,253 papers (3 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Self-Supervised Learning (8,965)
Adversarial Learning (5,204)
Unsupervised Learning (4,874)
Transfer Learning (4,808)
Weakly Supervised Learning (3,938)
Contrastive Learning (3,748)
Zero-Shot Learning (3,130)
Semi-Supervised Learning (3,128)
Reinforcement Learning (3,118)
Multi-Task Learning (2,556)
Evaluation (2,164)
Continual Learning (2,107)
Active Learning (1,983)
Few-Shot Learning (1,840)
Deep Learning (1,404)
Online Learning (1,360)
Multi-Armed Bandits (1,327)
Multimodal Learning (1,289)
Supervised Learning (986)
Multi-Agent Systems (813)
Uncertainty Quantification (805)
Causal Inference (636)
Robustness (576)
Retrieval-Augmented Generation (565)
Fine-Tuning (490)
Ensemble Learning (482)
In-Context Learning (439)
Multi-Label Classification (430)
Imitation Learning (387)
Prompt Engineering (270)
Multi-Lingual Learning (269)
Distribution Shift (264)
Reinforcement Learning from Human Feedback (209)
Regularization (207)
Exploration-Exploitation (203)
Generative Models (200)
Multi-Objective Optimization (185)
Out-of-Distribution Detection (176)
Sparse Learning (165)
Sampling (150)
Preference Learning (136)
Offline Reinforcement Learning (130)
Multi-Label Learning (128)
Markov Decision Process (127)
Neural Architecture Search (122)
Multi-Instance Learning (121)
Multi-View Learning (117)
Robust Learning (110)
Generative Model (110)
Time Series (108)
Large Language Models (104)
Exploration (103)
Hyperparameter Optimization (99)
Machine Unlearning (95)
Imbalanced Learning (93)
Machine Translation (93)
Multi-Class Classification (85)
Differential Privacy (82)
Time Series Analysis (71)
Reasoning (70)
Calibration (67)
Structure Learning (66)
Physics-Informed Learning (62)
Class Imbalance (58)
Model-Based RL (55)
Interactive Learning (55)
Multi-Domain Learning (47)
Inverse Reinforcement Learning (46)
Crowdsourcing (40)
Off-Policy Learning (38)
Label Noise (38)
Noisy Label Learning (35)
Offline RL (32)
Attention (32)
Evolutionary Algorithm (32)
Decision Making (31)
Policy Learning (30)
Personalization (28)
Low-Resource Learning (26)
Collaborative Filtering (25)
Self-Training (24)
Sequential Modeling (24)
Parameter Estimation (23)
Survival Analysis (21)
Machine Learning (20)
Parameter-Efficient Fine-Tuning (20)
Synthetic Data Generation (20)
Annotation (18)
Symbolic Regression (18)
AutoML (16)
Security (15)
Multi-Source Learning (13)
Distant Supervision (13)
Text Generation (11)
Distributional Reinforcement Learning (9)
Sentiment Analysis (9)
Multi-Hop Reasoning (9)
Language Modeling (9)
Code Generation (8)
Multi-Object Tracking (8)
Natural Language Inference (7)
Chain-of-Thought (6)
Question Answering (5)
Papers per year
1
8
12
26
18
20
135
136
147
149
220
231
316
526
460
477
660
1,314
2,083
3,689
4,652
5,914
6,826
8,201
8,755
9,258
2,019
2000
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Papers (including subtopics)
DocFinQA: A Long-Context Financial Reasoning Dataset
ACL 2024
DocNLC: A Document Image Enhancement Framework with Normalized and Latent Contrastive Representation for Multiple Degradations
AAAI 2024
DOC-RAG: ASR Language Model Personalization with Domain-Distributed Co-occurrence Retrieval Augmentation
COLING 2024
DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks
CVPR 2024
DocScript: Document-level Script Event Prediction
COLING 2024
Document Hashing with Multi-Grained Prototype-Induced Hierarchical Generative Model
EMNLP 2024
Document Set Expansion with Positive-Unlabeled Learning Using Intractable Density Estimation
COLING 2024
Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better
ACL 2024
Does Few-Shot Learning Suffer from Backdoor Attacks?
AAAI 2024
Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
EMNLP 2024
Does the Order Matter? Curriculum Learning over Languages
COLING 2024
DOFEN: Deep Oblivious Forest ENsemble
NeurIPS 2024
DoFIT: Domain-aware Federated Instruction Tuning with Alleviated Catastrophic Forgetting
NeurIPS 2024
Do Generated Data Always Help Contrastive Learning?
ICLR 2024
Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA
EMNLP 2024
Do large language models and humans have similar behaviours in causal inference with script knowledge?
NAACL 2024
Do Large Language Models Know How Much They Know?
EMNLP 2024
Do Llamas Work in English? On the Latent Language of Multilingual Transformers
ACL 2024
Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models
EMNLP 2024
Do LLMs suffer from Multi-Party Hangover? A Diagnostic Approach to Addressee Recognition and Response Selection in Conversations
EMNLP 2024
Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis
EMNLP 2024
Dolomites@#SMM4H 2024: Helping LLMs “Know The Drill” in Low-Resource Settings - A Study on Social Media Posts
ACL 2024
Domain Adaptation for Contrastive Audio-Language Models
Interspeech 2024
Domain Adaptation for Dense Retrieval and Conversational Dense Retrieval through Self-Supervision by Meticulous Pseudo-Relevance Labeling
COLING 2024
Domain Adaptation for Subjective Induction Questions Answering on Products by Adversarial Disentangled Learning
ACL 2024