📰 Workshop on Representation Learning for NLP 2025 — accepted papers

Workshop on Representation Learning for NLP 2025 is the 2025 edition of the Workshop on Representation Learning for NLP, held in Albuquerque, NM, May 2025 (publisher: Association for Computational Linguistics). The ACL Anthology lists 14 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. Amuro & Char: Analyzing the Relationship between Pre-Training and Fine-Tuning of Large Language ModelsKaiser Sun, Mark Dredze3 citations
2. Cross-Modal Learning for Music-to-Music-Video Description GenerationZhuoyuan Mao, Mengjie Zhao, Qiyu Wu et al.1 citation
3. Punctuation Restoration Improves Structure Understanding without SupervisionJunghyun Min, Minho Lee, Woochul Lee et al.1 citation

All accepted papers (14)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. Amuro & Char: Analyzing the Relationship between Pre-Training and Fine-Tuning of Large Language ModelsKaiser Sun, Mark Dredze3 citations
2. Cross-Modal Learning for Music-to-Music-Video Description GenerationZhuoyuan Mao, Mengjie Zhao, Qiyu Wu et al.1 citation
3. Punctuation Restoration Improves Structure Understanding without SupervisionJunghyun Min, Minho Lee, Woochul Lee et al.1 citation
4. A Comparative Study of Learning Paradigms in Large Language Models via Intrinsic DimensionSaahith Janapati, Yangfeng Ji
5. Choose Your Words Wisely: Domain-adaptive Masking Makes Language Models Learn FasterVanshpreet S. Kohli, Aaron Monis, Radhika Mamidi
6. DEPTH: Discourse Education through Pre-Training HierarchicallyZachary Elisha Bamberger, Ofek Glick, Chaim Baskin et al.
7. Efficient Document-level Event Relation ExtractionRuochen Li, Zimu Wang, Xinya Du
8. Investigating Adapters for Parameter-efficient Low-resource Automatic Speech RecognitionAhnaf Mozib Samin, Shekhar Nayak, Andrea De Marco et al.
9. Large Language Models Are Overparameterized Text EncodersThennal D K, Tim Fischer, Chris Biemann
10. Prompt Tuning Can Simply Adapt Large Language Models to Text EncodersKaiyan Zhao, Qiyu Wu, Zhongtao Miao et al.
11. Reverse Probing: Evaluating Knowledge Transfer via Finetuned Task Embeddings for Coreference ResolutionTatiana Anikina, Arne Binder, David Harbecke et al.our summary
12. State Space Models are Strong Text RerankersZhichao Xu, Jinghua Yan, Ashim Gupta et al.
13. Tracking Universal Features Through Fine-Tuning and Model MergingNiels Nielsen Horn, Desmond Elliott
14. Vocabulary-level Memory Efficiency for Language Model Fine-tuningMiles Williams, Nikolaos Aletras

📄 Papers with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. Reverse Probing: Evaluating Knowledge Transfer via Finetuned Task Embeddings for Coreference ResolutionWorkshop on Representation Learning for NLPTatiana Anikina, Arne Binder, David Harbecke, et al.2025

🧭 Top topics

Topics of its works in our library, with the number of works on each.

🔗Coreference resolution (1)🔬Interpretability (1)

📚 Fields

🎭Arts and Humanities (1)🖥️Computer Science (1)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🔬German Research Centre for Artificial IntelligenceKaiserslautern · Germany1 work here🎓Technische Universität BerlinBerlin · Germany1 work here🎓Saarland UniversitySaarbrücken · Germany1 work here

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

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