NLPExplorer

RepL4NLP - 2025

Total Papers:- 15

Total Papers accross all years:- 121

Total Citations :- 0

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Proceedings of the 10th Workshop on Representation Learning for NLP (RepL4NLP-2025)

Efficient Document-level Event Relation Extraction

Ruochen Li | Zimu Wang | Xinya Du |

Large Language Models Are Overparameterized Text Encoders

Thennal D K | Tim Fischer | Chris Biemann |

Tracking Universal Features Through Fine-Tuning and Model Merging

Niels Nielsen Horn | Desmond Elliott |

DEPTH: Discourse Education through Pre-Training Hierarchically

Zachary Elisha Bamberger | Ofek Glick | Chaim Baskin | Yonatan Belinkov |

Investigating Adapters for Parameter-efficient Low-resource Automatic Speech Recognition

Ahnaf Mozib Samin | Shekhar Nayak | Andrea De Marco | Claudia Borg |

Vocabulary-level Memory Efficiency for Language Model Fine-tuning

Miles Williams | Nikolaos Aletras |

Reverse Probing: Evaluating Knowledge Transfer via Finetuned Task Embeddings for Coreference Resolution

Amuro & Char: Analyzing the Relationship between Pre-Training and Fine-Tuning of Large Language Models

Kaiser Sun | Mark Dredze |

State Space Models are Strong Text Rerankers

Zhichao Xu | Jinghua Yan | Ashim Gupta | Vivek Srikumar |

Prompt Tuning Can Simply Adapt Large Language Models to Text Encoders

Kaiyan Zhao | Qiyu Wu | Zhongtao Miao | Yoshimasa Tsuruoka |

Cross-Modal Learning for Music-to-Music-Video Description Generation

A Comparative Study of Learning Paradigms in Large Language Models via Intrinsic Dimension

Saahith Janapati | Yangfeng Ji |

Punctuation Restoration Improves Structure Understanding without Supervision

Junghyun Min | Minho Lee | Lee Woochul | Yeonsoo Lee |