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Methodology
← Learning Types
Machine Learning
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Representation Learning
2843 directly classified papers
Papers per year
2002: 1
2005: 2
2006: 5
2007: 11
2008: 12
2009: 10
2010: 6
2011: 6
2012: 30
2013: 36
2014: 34
2015: 20
2016: 42
2017: 82
2018: 128
2019: 189
2020: 266
2021: 279
2022: 382
2023: 358
2024: 451
2025: 486
2026: 7
Papers
The Benefits of Mixup for Feature Learning
ICML 2023
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation
ICML 2023
Patch-level Contrastive Learning via Positional Query for Visual Pre-training
ICML 2023
Disentangled Phonetic Representation for Chinese Spelling Correction
ACL 2023
The Wisdom of Hindsight Makes Language Models Better Instruction Followers
ICML 2023
Global Mixup: Eliminating Ambiguity with Clustering
AAAI 2023
Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modeling
ICML 2023
When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations
ICML 2023
CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models
ICML 2023
RFiD: Towards Rational Fusion-in-Decoder for Open-Domain Question Answering
ACL 2023
An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning
ICML 2023
Continual Learners are Incremental Model Generalizers
ICML 2023
ETHICIST: Targeted Training Data Extraction Through Loss Smoothed Soft Prompting and Calibrated Confidence Estimation
ACL 2023
Temporal Label Smoothing for Early Event Prediction
ICML 2023
Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks
ICML 2023
Multiview Identifiers Enhanced Generative Retrieval
ACL 2023
Language Model Analysis for Ontology Subsumption Inference
ACL 2023
Parametric Information Maximization for Generalized Category Discovery
ICCV 2023
Optimizing Mode Connectivity for Class Incremental Learning
ICML 2023
Reachability-Aware Laplacian Representation in Reinforcement Learning
ICML 2023
What is the best recipe for character-level encoder-only modelling?
ACL 2023
Curriculum Co-disentangled Representation Learning across Multiple Environments for Social Recommendation
ICML 2023
RGE: A Repulsive Graph Rectification for Node Classification via Influence
ICML 2023
BERM: Training the Balanced and Extractable Representation for Matching to Improve Generalization Ability of Dense Retrieval
ACL 2023
The CRINGE Loss: Learning what language not to model
ACL 2023
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