← Core Methods
Machine Learning › Core Methods ›

Representation Learning

18863 directly classified papers

Papers per year

Papers

What does memory retrieval leave on the table? Modelling the Cost of Semi-Compositionality with MINERVA2 and sBERT ACL 2025
High-Dimensional Interlingual Representations of Large Language Models ACL 2025
Weight-of-Thought Reasoning: Exploring Neural Network Weights for Enhanced LLM Reasoning ACL 2025
Inductive Learning on Heterogeneous Graphs Enhanced by LLMs for Software Mention Detection ACL 2025
Document Attribution: Examining Citation Relationships using Large Language Models ACL 2025
Pre-trained Language Models Learn Remarkably Accurate Representations of Numbers EMNLP 2025
V-VAE: A Variational Auto Encoding Framework Towards Fine-Grained Control over Human-Like Chat EMNLP 2025
DIACU: A dataset for the DIAchronic analysis of Church Slavonic ACL 2025
Enhanced Denesity Peak Clustering for High-Dimensional Data AAAI 2025
Construction Identification and Disambiguation Using BERT: A Case Study of NPN ACL 2025
Derivational Probing: Unveiling the Layer-wise Derivation of Syntactic Structures in Neural Language Models ACL 2025
3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding ICCV 2025
Disentangling Biased Representations: A Causal Intervention Framework for Fairer NLP Models ACL 2025
Unsupervised Concept Vector Extraction for Bias Control in LLMs EMNLP 2025
INT: Establishing Information Transfer for Multilingual Intent Detection and Slot Filling ACL 2025
The Strawberry Problem: Emergence of Character-level Understanding in Tokenized Language Models EMNLP 2025
Type-Less yet Type-Aware Inductive Link Prediction with Pretrained Language Models EMNLP 2025
Toward Efficient Sparse Autoencoder-Guided Steering for Improved In-Context Learning in Large Language Models EMNLP 2025
Probing and Boosting Large Language Models Capabilities via Attention Heads EMNLP 2025
Using Machine Learning to Improve Research in the Agriculture Industry AAAI 2025
Explaining Differences Between Model Pairs in Natural Language through Sample Learning EMNLP 2025
Mixture of Languages: Improved Multilingual Encoders Through Language Grouping EMNLP 2025
Multimodal Invariant Sentiment Representation Learning ACL 2025
Synergy of GFlowNet and Protein Language Model Makes a Diverse Antibody Designer AAAI 2025
Can Machines Understand Composition? Dataset and Benchmark for Photographic Image Composition Embedding and Understanding CVPR 2025