Papers
Research papers from arXiv and related sources
Predicting the Peak Energy of Swift Gamma-Ray Bursts Using Supervised Machine Learning
Gamma-ray bursts (GRBs) are among the most energetic explosive phenomena in the universe, and their peak energy ($E_{\rm p}$) is a key physical quantity for understanding the prompt emission mechan...
Wan-Peng Sun, Si-Yuan Zhu, Da-Ling Ma, Fu-Wen Zhang
Diagnosing Generalization Failures from Representational Geometry Markers
Generalization, the ability to perform well beyond the training context, is a hallmark of biological and artificial intelligence, yet anticipating unseen failures remains a central challenge. Conve...
Chi-Ning Chou, Artem Kirsanov, Yao-Yuan Yang, SueYeon Chung
CTForensics: A Comprehensive Dataset and Method for AI-Generated CT Image Detection
With the rapid development of generative AI in medical imaging, synthetic Computed Tomography (CT) images have demonstrated great potential in applications such as data augmentation and clinical di...
Yiheng Li, Zichang Tan, Guoqing Xu, Yijun Ye, Yang Yang, Zhen Lei
KDFlow: A User-Friendly and Efficient Knowledge Distillation Framework for Large Language Models
Knowledge distillation (KD) is an essential technique to compress large language models (LLMs) into smaller ones. However, despite the distinct roles of the student model and the teacher model in K...
Songming Zhang, Xue Zhang, Tong Zhang, Bojie Hu, Yufeng Chen, Jinan Xu
Phishing the Phishers with SpecularNet: Hierarchical Graph Autoencoding for Reference-Free Web Phishing Detection
Phishing remains the most pervasive threat to the Web, enabling large-scale credential theft and financial fraud through deceptive webpages. While recent reference-based and generative-AI-driven ph...
Tailai Song, Pedro Casas, Michela Meo
Guaranteed Image Classification via Goal-oriented Joint Semantic Source and Channel Coding
To enable critical applications such as remote diagnostics, image classification must be guaranteed under bandwidth constraints and unreliable wireless channels through joint source and channel cod...
Wenchao Wu, Min Qiu, Yansha Deng, Jinhong Yuan
Sovereign AI-based Public Services are Viable and Affordable
The rapid expansion of AI-based remote services has intensified debates about the long-term implications of growing structural concentration in infrastructure and expertise. As AI capabilities beco...
António Branco, Luís Gomes, Rodrigo Santos, Eduardo Santos, João Silva, Nuno Marques, Madalena Ro...
Absolute scintillator light yield correction for SiPIN readout via Transfer Matrix Method and Geant4 optical simulation
Precise measurement of the absolute light yield (LY) of scintillators has long been limited by systematic effects inherent in realistic readout geometries. Large-angle incidence, multiple reflectio...
Ge Ma, Zhiyang Yuan, Chencheng Feng, Zirui Yang, Zhenwei Yang, Ming Zeng
CyclicJudge: Mitigating Judge Bias Efficiently in LLM-based Evaluation
LLM-as-judge evaluation has become standard practice for open-ended model assessment; however, judges exhibit systematic biases that cannot be eliminated by increasing the number of scenarios or ge...
Ziyi Zhu, Olivier Tieleman, Alexey Bukhtiyarov, Jinghong Chen
Decoupling of topology and texture in optical skyrmions under turbulence
Topological structure is widely invoked as a route to disorder-resilient photonic states, yet whether it protects locally resolved field structure under realistic disorder has not been established....
D. G. Pires, N. M. Litchinitser
Let the Agent Search: Autonomous Exploration Beats Rigid Workflows in Temporal Question Answering
Temporal Knowledge Graph Question Answering (TKGQA) demands multi-hop reasoning under temporal constraints. Prior approaches based on large language models (LLMs) typically rely on rigid, hand-craf...
Xufei Lv, Jiahui Yang, Yifu Gao, Linbo Qiao, Houde Liu
Defect dependent dynamic nanoindentation hardness of copper up to 25 000 s-1
Metals exhibit an upturn in strength at strain rates of approximately 1000 s-1 - 3000 s-1, governed by rapid dislocation multiplication, interactions and storage. This phenomenon is strongly influe...
Hendrik Holz, Lalith Kumar Bhaskar, Tobias Brink, Dipali Sonowane, Gerhard Dehm, James P. Best, R...
On Channel Model to Bridge the Gap between MIMO Design and Performance Requirements in 3GPP
Accurate channel modeling has become critical for evaluating multiple-input multiple-output (MIMO) performance, especially as 5G standardization matures and efforts toward 6G begin. Recent studies ...
Lynda Berrah, Raphael Visoz, Didier Le Ruyet, Anvar Tukmanov, Axel Müeller, Alexander Hamilton, M...
Uniform-in-time concentration in two-layer neural networks via transportation inequalities
We quantify, uniformly over time and with high probability, the discrepancy between the predictions of a two-layer neural network trained by stochastic gradient descent (SGD) and their mean-field l...
Arnaud Guillin, Boris Nectoux, Paul Stos
Constrained Particle Seeking: Solving Diffusion Inverse Problems with Just Forward Passes
Diffusion models have gained prominence as powerful generative tools for solving inverse problems due to their ability to model complex data distributions. However, existing methods typically rely ...
Hongkun Dou, Zike Chen, Zeyu Li, Hongjue Li, Lijun Yang, Yue Deng
Affine Correspondences in Stereo Vision: Theory, Practice, and Limitations
Affine transformations have been recently used for stereo vision. They can be exploited in various computer vision application, e.g., when estimating surface normals, homographies, fundamental and ...
Levente Hajder
Probing Materials Knowledge in LLMs: From Latent Embeddings to Reliable Predictions
Large language models are increasingly applied to materials science, yet fundamental questions remain about their reliability and knowledge encoding. Evaluating 25 LLMs across four materials scienc...
Vineeth Venugopal, Soroush Mahjoubi, Elsa Olivetti
OpenAutoNLU: Open Source AutoML Library for NLU
OpenAutoNLU is an open-source automated machine learning library for natural language understanding (NLU) tasks, covering both text classification and named entity recognition (NER). Unlike existin...
Grigory Arshinov, Aleksandr Boriskin, Sergey Senichev, Ayaz Zaripov, Daria Galimzianova, Daniil K...
Emerging Human-like Strategies for Semantic Memory Foraging in Large Language Models
Both humans and Large Language Models (LLMs) store a vast repository of semantic memories. In humans, efficient and strategic access to this memory store is a critical foundation for a variety of c...
Eric Lacosse, Mariana Duarte, Peter M. Todd, Daniel C. McNamee
Voices, Faces, and Feelings: Multi-modal Emotion-Cognition Captioning for Mental Health Understanding
Emotional and cognitive factors are essential for understanding mental health disorders. However, existing methods often treat multi-modal data as classification tasks, limiting interpretability es...
Zhiyuan Zhou, Yanrong Guo, Shijie Hao