Tootfinder

Efficient Multilingual ASR Finetuning via LoRA Language Experts
Jiahong Li, Yiwen Shao, Jianheng Zhuo, Chenda Li, Liliang Tang, Dong Yu, Yanmin Qian
https://arxiv.org/abs/2506.21555

Efficient Multilingual ASR Finetuning via LoRA Language Experts
Recent advancements in deep learning have significantly enhanced multilingual automatic speech recognition (ASR) due to the development of advanced model architectures and available large-scale multilingual datasets. Despite that, multilingual ASR still suffers from the curse of multilinguality in that different languages tend to interfere with each other, making it difficult for the ASR model to identify multiple languages effectively while sharing model capacity across them. This paper propos…

physics_collab: Multilayer physicist collaborations (2015)
Two multiplex networks of coauthorships among the Pierre Auger Collaboration of physicists (2010-2012) and among researchers who have posted preprints on arXiv.org (all papers up to May 2014). Layers represent different categories of publication, and an edge's weight indicates the number of reports written by the authors. These layers are one-mode projections from the underlying author-paper bipartite network.
This n…

Change Point Localization and Inference in Dynamic Multilayer Networks
Fan Wang, Kyle Ritscher, Yik Lun Kei, Xin Ma, Oscar Hernan Madrid Padilla
https://arxiv.org/abs/2506.21878

Change Point Localization and Inference in Dynamic Multilayer Networks
We study offline change point localization and inference in dynamic multilayer random dot product graphs (D-MRDPGs), where at each time point, a multilayer network is observed with shared node latent positions and time-varying, layer-specific connectivity patterns. We propose a novel two-stage algorithm that combines seeded binary segmentation with low-rank tensor estimation, and establish its consistency in estimating both the number and locations of change points. Furthermore, we derive the l…

VeS: Teaching Pixels to Listen Without Supervision
Sajay Raj
https://arxiv.org/abs/2507.22008 https://arxiv.org/pdf/2507.22008

VeS: Teaching Pixels to Listen Without Supervision
Recent dense audio-visual (AV) models achieve impressive retrieval and emergent localization, but almost all evidence comes from English-centric, caption-rich web video. It is unclear whether these objectives survive in low-resource, code-switched, and noisy multilingual settings that typify developing regions. We show they do**-**and that the choice of aggregation function becomes even more critical. Using a multilingual subset of Project Vaani spanning dozens of Indian languages and dialectal…

X-ray diffraction from smectic multilayers: crossover from kinematical to dynamical regime
V. V. Samsonov, K. V. Nikolaev, B. I. Ostrovskii, S. N. Yakunin
https://arxiv.org/abs/2505.23547

X-ray diffraction from smectic multilayers: crossover from kinematical to dynamical regime
We study X-ray diffraction in smectic liquid crystal multilayers. Such systems are fabricated as freely suspended films and have a unique layered structure. As such, they can be described as organic Bragg mirrors with sub-nanometer roughness. However, an interesting peculiarity arises in the diffraction on these structures: the characteristic shape of diffraction peaks associated with dynamical scattering effects is not observed. Instead, the diffraction can be well described kinematically, whi…

Mildly interesting: Der #Gasspeicher #Rehden ist wieder leer. Zuletzt passierte das 2021/2022 unter Gazprom und quasi-Russischer Kontrolle. Aktuell gäbe es Angebot, Preise sind etwa auf Vorjahresniveau. Wäre interessant zu wissen, warum der aktuelle Betreiber den Sommer nicht fürs Nachf…

Multilingual JobBERT for Cross-Lingual Job Title Matching
Jens-Joris Decorte, Matthias De Lange, Jeroen Van Hautte
https://arxiv.org/abs/2507.21609 https://

Multilingual JobBERT for Cross-Lingual Job Title Matching
We introduce JobBERT-V3, a contrastive learning-based model for cross-lingual job title matching. Building on the state-of-the-art monolingual JobBERT-V2, our approach extends support to English, German, Spanish, and Chinese by leveraging synthetic translations and a balanced multilingual dataset of over 21 million job titles. The model retains the efficiency-focused architecture of its predecessor while enabling robust alignment across languages without requiring task-specific supervision. Ext…

physics_collab: Multilayer physicist collaborations (2015)
Two multiplex networks of coauthorships among the Pierre Auger Collaboration of physicists (2010-2012) and among researchers who have posted preprints on arXiv.org (all papers up to May 2014). Layers represent different categories of publication, and an edge's weight indicates the number of reports written by the authors. These layers are one-mode projections from the underlying author-paper bipartite network.
This n…

physics_collab: Multilayer physicist collaborations (2015)
Two multiplex networks of coauthorships among the Pierre Auger Collaboration of physicists (2010-2012) and among researchers who have posted preprints on arXiv.org (all papers up to May 2014). Layers represent different categories of publication, and an edge's weight indicates the number of reports written by the authors. These layers are one-mode projections from the underlying author-paper bipartite network.
This n…

Multilingual Political Views of Large Language Models: Identification and Steering
Daniil Gurgurov, Katharina Trinley, Ivan Vykopal, Josef van Genabith, Simon Ostermann, Roberto Zamparelli
https://arxiv.org/abs/2507.22623

Multilingual Political Views of Large Language Models: Identification and Steering
Large language models (LLMs) are increasingly used in everyday tools and applications, raising concerns about their potential influence on political views. While prior research has shown that LLMs often exhibit measurable political biases--frequently skewing toward liberal or progressive positions--key gaps remain. Most existing studies evaluate only a narrow set of models and languages, leaving open questions about the generalizability of political biases across architectures, scales, and mult…