NLPExplorer

RepL4NLP - 2024

Total Papers:- 23

Total Papers accross all years:- 106

Total Citations :- 0

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Word Boundary Information Isn’t Useful for Encoder Language Models

How Useful is Continued Pre-Training for Generative Unsupervised Domain Adaptation?

Rheeya Uppaal | Yixuan Li | Junjie Hu |

Prior Knowledge-Guided Adversarial Training

Learn it or Leave it: Module Composition and Pruning for Continual Learning

DomainInv: Domain Invariant Fine Tuning and Adversarial Label Correction For Unsupervised QA Domain Adaptation

Anant Khandelwal |

Text-Guided Alternative Image Clustering

Relevance-aware Diverse Query Generation for Out-of-domain Text Ranking

Learning Contextualized Box Embeddings with Prototypical Networks

Kohei Oda | Kiyoaki Shirai | Natthawut Kertkeidkachorn |

Proceedings of the 9th Workshop on Representation Learning for NLP (RepL4NLP-2024)

Learning New Tasks from a Few Examples with Soft-Label Prototypes

Avyav Singh | Ekaterina Shutova | Helen Yannakoudakis |

QAVSA: Question Answering using Vector Symbolic Algebras

Ryan Laube | Chris Eliasmith |

Multi-label Learning with Random Circular Vectors

Learning from Others: Similarity-based Regularization for Mitigating Dataset Bias.

Reda Igbaria | Yonatan Belinkov |

Tracking linguistic information in transformer-based sentence embeddings through targeted sparsification

Vivi Nastase | Paola Merlo |