1 citations · 1 across the 12 of their papers we have counts for
13 papers
Embedding Models Measure in Peculiar Ways
Juri Opitz, Andrianos Michail
Embedding spaces define notions of semantic similarity and distance. We study whether those embeddings reflect physical measurements of mass, distance, time and volume, which admit…
ALEE: Any-Language Evaluation of Embeddings via English-Centric Minimal Pairs
Andrianos Michail, Stylianos Psychias, Michelle Wastl +3
Text embeddings are standard for semantic similarity tasks, yet their evaluation remains an open challenge. Current benchmarks are static, cover only a limited set of languages, ar…
Exploring Dowker Homology for Sentence Similarity
Marius Huber, Juri Opitz
Dowker homology is a topological tool that may be used to analyze the relative position of two point clouds living in a common space. We investigate whether Dowker homology capture…
ICDAR 2026 HIPE-OCRepair Competition on LLM-Assisted OCR Post-Correction for Historical Documents
Maud Ehrmann, Emanuela Boros, Juri Opitz +3
We present the results of HIPE-OCRepair-2026, an ICDAR competition on LLM-assisted OCR post-correction of historical documents. OCR post-correction remains a long-standing challeng…
Overview of HIPE-2026: Person-Place Relation Extraction from Multilingual Historical Texts
Juri Opitz, Maud Ehrmann, Corina Raclé +3
Was this person ever at that place, and if so, when? Answering such questions from noisy, multilingual historical documents is the central challenge of HIPE-2026, the third edition…
Attention Calibration for Position-Fair Dense Retrieval
Andrianos Michail, Elias Schuhmacher, Juri Opitz +2
Dense retrieval compresses a passage into a single vector, but this compression is positionally skewed: early content dominates the embedding, and retrieval degrades when the relev…
CLEF HIPE-2026: Evaluating Accurate and Efficient Person-Place Relation Extraction from Multilingual Historical Texts
Juri Opitz, Corina Raclé, Emanuela Boros +4
HIPE-2026 is a CLEF evaluation lab dedicated to person-place relation extraction from noisy, multilingual historical texts. Building on the HIPE-2020 and HIPE-2022 campaigns, it ex…
Information Representation Fairness in Long-Document Embeddings: The Peculiar Interaction of Positional and Language Bias
Elias Schuhmacher, Andrianos Michail, Juri Opitz +2
To be discoverable in an embedding-based search process, each part of a document should be reflected in its embedding representation. To quantify any potential reflection biases, w…
Mechanistic Decomposition of Sentence Representations
Matthieu Tehenan, Vikram Natarajan, Jonathan Michala +2
Sentence embeddings are central to modern NLP and AI systems, yet little is known about their internal structure. While we can compare these embeddings using measures such as cosin…
Adapting Multilingual Embedding Models to Historical Luxembourgish
Andrianos Michail, Corina Julia Raclé, Juri Opitz +1
The growing volume of digitized historical texts requires effective semantic search using text embeddings. However, pre-trained multilingual models face challenges with historical…
Interpretable Text Embeddings and Text Similarity Explanation: A Survey
Juri Opitz, Lucas Möller, Andrianos Michail +2
Text embeddings are a fundamental component in many NLP tasks, including classification, regression, clustering, and semantic search. However, despite their ubiquitous application,…
Sentence Smith: Controllable Edits for Evaluating Text Embeddings
Hongji Li, Andrianos Michail, Reto Gubelmann +2
Controllable and transparent text generation has been a long-standing goal in NLP. Almost as long-standing is a general idea for addressing this challenge: Parsing text to a symbol…
PARAPHRASUS : A Comprehensive Benchmark for Evaluating Paraphrase Detection Models
Andrianos Michail, Simon Clematide, Juri Opitz
The task of determining whether two texts are paraphrases has long been a challenge in NLP. However, the prevailing notion of paraphrase is often quite simplistic, offering only a…