Papers
Research papers from arXiv and related sources
Modeling the Senegalese artisanal fisheries migrations
The North-West African coast is enriched by the Canary current, which sustain a very produc- tive marine ecosystem. The Senegalese artisanal fishing fleet, the largest in West Africa, ben- efit fro...
Alassane Bah, Timothée Brochier
SERQ: Saliency-Aware Low-Rank Error Reconstruction for LLM Quantization
Post-training quantization (PTQ) has emerged as a prevailing technique for deploying large language models (LLMs) efficiently in terms of both memory and computation, across edge devices and server...
Yeonsik Park, Hyeonseong Kim, Seungkyu Choi
Soft Fault Estimation and Localisation in Y-Shaped Networks using OFDM-Based Signals
This paper introduces a method for detecting, estimating, and localising a soft fault in wired communication networks. The proposed method is based on analysing the transmission coefficients (TC) i...
Ameer Ahmadie, Ndeye Gueye, Virginie Degardin, Vincent Cocquempot
TildeOpen LLM: Leveraging Curriculum Learning to Achieve Equitable Language Representation
Large language models often underperform in many European languages due to the dominance of English and a few high-resource languages in training data. This paper presents TildeOpen LLM, a 30-billi...
Toms Bergmanis, Martins Kronis, Ingus Jānis Pretkalniņš, Dāvis Nicmanis, Jeļizaveta Jeļinska, Rob...
AutoAdapt: An Automated Domain Adaptation Framework for LLMs
Large language models (LLMs) excel in open domains but struggle in specialized settings with limited data and evolving knowledge. Existing domain adaptation practices rely heavily on manual trial-a...
Sidharth Sinha, Anson Bastos, Xuchao Zhang, Akshay Nambi, Chetan Bansal, Saravan Rajmohan
Privacy-Preserving End-to-End Full-Duplex Speech Dialogue Models
End-to-end full-duplex speech models feed user audio through an always-on LLM backbone, yet the speaker privacy implications of their hidden representations remain unexamined. Following the VoicePr...
Nikita Kuzmin, Tao Zhong, Jiajun Deng, Yingke Zhu, Tristan Tsoi, Tianxiang Cao, Simon Lui, Kong A...
MERLIN: Building Low-SNR Robust Multimodal LLMs for Electromagnetic Signals
The paradigm of Multimodal Large Language Models (MLLMs) offers a promising blueprint for advancing the electromagnetic (EM) domain. However, prevailing approaches often deviate from the native MLL...
Junyu Shen, Zhendong She, Chenghanyu Zhang, Yuchuang Sun, Luqing Luo, Dingwei Tan, Zonghao Guo, B...
Evidence-Driven Reasoning for Industrial Maintenance Using Heterogeneous Data
Industrial maintenance platforms contain rich but fragmented evidence, including free-text work orders, heterogeneous operational sensors or indicators, and structured failure knowledge. These sour...
Fearghal O'Donncha, Nianjun Zhou, Natalia Martinez, James T Rayfield, Fenno F. Heath, Abigail Lan...
SiPM non-linearity studies in beam tests with scintillating crystals
High-granularity homogeneous electromagnetic calorimeters based on scintillating crystals and silicon photomultipliers (SiPMs) are a promising option for future $e^{+}e^{-}$ Higgs factories, where ...
Zhiyu Zhao, Dejing Du, Shu Li, Yong Liu, Baohua Qi, Jack Rolph, Haijun Yang
RexDrug: Reliable Multi-Drug Combination Extraction through Reasoning-Enhanced LLMs
Automated Drug Combination Extraction (DCE) from large-scale biomedical literature is crucial for advancing precision medicine and pharmacological research. However, existing relation extraction me...
Zhijun Wang, Ling Luo, Dinghao Pan, Huan Zhuang, Lejing Yu, Yuanyuan Sun, Hongfei Lin
An explainable hybrid deep learning-enabled intelligent fault detection and diagnosis approach for automotive software systems validation
Advancements in data-driven machine learning have emerged as a pivotal element in supporting automotive software systems (ASSs) engineering across various levels of the V-development process. Durin...
Mohammad Abboush, Ehab Ghannoum, Andreas Rausch
The Differential Effects of Agreeableness and Extraversion on Older Adults' Perceptions of Conversational AI Explanations in Assistive Settings
Large Language Model-based Voice Assistants (LLM-VAs) are increasingly deployed in assistive settings for older adults, yet little is known about how an agent's personality shapes user perceptions ...
Niharika Mathur, Hasibur Rahman, Smit Desai
Covenant-72B: Pre-Training a 72B LLM with Trustless Peers Over-the-Internet
Recently, there has been increased interest in globally distributed training, which has the promise to both reduce training costs and democratize participation in building large-scale foundation mo...
Joel Lidin, Amir Sarfi, Erfan Miahi, Quentin Anthony, Shivam Chauhan, Evangelos Pappas, Benjamin ...
Learning Hierarchical Knowledge in Text-Rich Networks with Taxonomy-Informed Representation Learning
Hierarchical knowledge structures are ubiquitous across real-world domains and play a vital role in organizing information from coarse to fine semantic levels. While such structures have been widel...
Yunhui Liu, Yongchao Liu, Yinfeng Chen, Chuntao Hong, Tao Zheng, Tieke He
Gender Bias in MT for a Genderless Language: New Benchmarks for Basque
Large language models (LLMs) and machine translation (MT) systems are increasingly used in our daily lives, but their outputs can reproduce gender bias present in the training data. Most resources ...
Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez
Gradually Excavating External Knowledge for Implicit Complex Question Answering
Recently, large language models (LLMs) have gained much attention for the emergence of human-comparable capabilities and huge potential. However, for open-domain implicit question-answering problem...
Chang Liu, Xiaoguang Li, Lifeng Shang, Xin Jiang, Qun Liu, Edmund Y. Lam, Ngai Wong
Training event-based neural networks with exact gradients via Differentiable ODE Solving in JAX
Existing frameworks for gradient-based training of spiking neural networks face a trade-off: discrete-time methods using surrogate gradients support arbitrary neuron models but introduce gradient b...
Lukas König, Manuel Kuhn, David Kappel, Anand Subramoney
UniGround: Universal 3D Visual Grounding via Training-Free Scene Parsing
Understanding and localizing objects in complex 3D environments from natural language descriptions, known as 3D Visual Grounding (3DVG), is a foundational challenge in embodied AI, with broad impli...
Jiaxi Zhang, Yunheng Wang, Wei Lu, Taowen Wang, Weisheng Xu, Shuning Zhang, Yixiao Feng, Yuetong ...
EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery
The increasing adoption of Large Language Models (LLMs) has enabled AI scientists to perform complex end-to-end scientific discovery tasks requiring coordination of specialized roles, including ide...
Yougang Lyu, Xi Zhang, Xinhao Yi, Yuyue Zhao, Shuyu Guo, Wenxiang Hu, Jan Piotrowski, Jakub Kalis...
An improved measurement of $η^\prime\rightarrow e^{+}e^{-}ω$
Using a sample of $(10087 \pm 44) \times 10^{6}$ $J/ψ$ events collected with the BESIII detector, an improved measurement of the decay $η^{\prime}\rightarrow e^{+}e^{-}ω$, with $ω\rightarrowπ^{+}π^...
BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, C. S. Akondi, R. Alibert...