4 citations · 9 across the 12 of their papers we have counts for
12 papers
To MRL or not to MRL: Text Embeddings are Robust to Truncation Without Matryoshka Learning, Except In Heavy Truncation Scenarios
Sotaro Takeshita, Yurina Takeshita, Simone Paolo Ponzetto +1
Matryoshka Representation Learning (MRL) is a widely adopted approach for training text encoders so they provide useful text representations at various sizes, available by simply t…
CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data
Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94
Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…
GerAV: Towards New Heights in German Authorship Verification using Fine-Tuned LLMs on a New Benchmark
Lotta Kiefer, Christoph Leiter, Sotaro Takeshita +2
Authorship verification (AV) is the task of determining whether two texts were written by the same author and has been studied extensively, predominantly for English data. In contr…
SciLaD: A Large-Scale, Transparent, Reproducible Dataset for Natural Scientific Language Processing
Luca Foppiano, Sotaro Takeshita, Pedro Ortiz Suarez +6
SciLaD is a novel, large-scale dataset of scientific language constructed entirely using open-source frameworks and publicly available data sources. It comprises a curated English…
Randomly Removing 50% of Dimensions in Text Embeddings has Minimal Impact on Retrieval and Classification Tasks
Sotaro Takeshita, Yurina Takeshita, Daniel Ruffinelli +1
In this paper, we study the surprising impact that truncating text embeddings has on downstream performance. We consistently observe across 6 state-of-the-art text encoders and 26…
DeepSeek-R1 vs. o3-mini: How Well can Reasoning LLMs Evaluate MT and Summarization?
Daniil Larionov, Sotaro Takeshita, Ran Zhang +5
Reasoning-enabled large language models (LLMs) excel in logical tasks, yet their utility for evaluating natural language generation remains unexplored. This study systematically co…
ACLSum: A New Dataset for Aspect-based Summarization of Scientific Publications
Sotaro Takeshita, Tommaso Green, Ines Reinig +2
Extensive efforts in the past have been directed toward the development of summarization datasets. However, a predominant number of these resources have been (semi)-automatically g…
ROUGE-K: Do Your Summaries Have Keywords?
Sotaro Takeshita, Simone Paolo Ponzetto, Kai Eckert
Keywords, that is, content-relevant words in summaries play an important role in efficient information conveyance, making it critical to assess if system-generated summaries contai…
VADIS -- a VAriable Detection, Interlinking and Summarization system
Yavuz Selim Kartal, Muhammad Ahsan Shahid, Sotaro Takeshita +4
The VADIS system addresses the demand of providing enhanced information access in the domain of the social sciences. This is achieved by allowing users to search and use survey var…
Towards Automated Survey Variable Search and Summarization in Social Science Publications
Yavuz Selim Kartal, Sotaro Takeshita, Tornike Tsereteli +6
Nowadays there is a growing trend in many scientific disciplines to support researchers by providing enhanced information access through linking of publications and underlying data…
X-SCITLDR: Cross-Lingual Extreme Summarization of Scholarly Documents
Sotaro Takeshita, Tommaso Green, Niklas Friedrich +2
The number of scientific publications nowadays is rapidly increasing, causing information overload for researchers and making it hard for scholars to keep up to date with current t…
ZusammenQA: Data Augmentation with Specialized Models for Cross-lingual Open-retrieval Question Answering System
Chia-Chien Hung, Tommaso Green, Robert Litschko +5
This paper introduces our proposed system for the MIA Shared Task on Cross-lingual Open-retrieval Question Answering (COQA). In this challenging scenario, given an input question t…