5 papers
Asymmetric Within-Document Predictive Learning for Scientific Document Representation
You Zuo, Éric de la Clergerie, Benoît Sagot
We study predictive pretraining for scientific document representation using the discourse structure of papers. We propose SciJEPA, a citation-free framework that learns through as…
Sparse Coverage: Semantic Center Representations for Patent Prior-Art Retrieval
You Zuo, Kim Gerdes, Éric de la Clergerie +1
Patent prior-art retrieval is a recall-oriented search task over long and highly structured technical documents. Dense retrieval improves semantic matching, but single-vector repre…
Citation-Driven Multi-View Training for Patent Embeddings: QaECTER and Sophia-Bench
Younes Djemmal, You Zuo, Kim Gerdes +1
Patent retrieval underpins critical decisions in innovation, examination, and IP strategy, yet progress has been hampered by the absence of benchmarks that reflect the diversity of…
Patent Representation Learning via Self-supervision
You Zuo, Kim Gerdes, Éric de la Clergerie +1
We study self-supervised patent representation learning with contrastive objectives. A standard baseline constructs positives by encoding the same text twice under independent drop…
PatentEval: Understanding Errors in Patent Generation
You Zuo, Kim Gerdes, Eric Villemonte de La Clergerie +1
In this work, we introduce a comprehensive error typology specifically designed for evaluating two distinct tasks in machine-generated patent texts: claims-to-abstract generation,…