Papers
Research papers from arXiv and related sources
EvolveCoder: Evolving Test Cases via Adversarial Verification for Code Reinforcement Learning
Reinforcement learning with verifiable rewards (RLVR) is a promising approach for improving code generation in large language models, but its effectiveness is limited by weak and static verificatio...
Chi Ruan, Dongfu Jiang, Huaye Zeng, Ping Nie, Wenhu Chen
RXNRECer Enables Fine-grained Enzymatic Function Annotation through Active Learning and Protein Language Models
A key challenge in enzyme annotation is identifying the biochemical reactions catalyzed by proteins. Most existing methods rely on Enzyme Commission (EC) numbers as intermediaries: they first predi...
Zhenkun Shi, Jun Zhu, Dehang Wang, BoYu Chen, Qianqian Yuan, Zhitao Mao, Fan Wei, Weining Wu, Xia...
STRAP-ViT: Segregated Tokens with Randomized -- Transformations for Defense against Adversarial Patches in ViTs
Adversarial patches are physically realizable localized noise, which are able to hijack Vision Transformers (ViT) self-attention, pulling focus toward a small, high-contrast region and corrupting t...
Nandish Chattopadhyay, Anadi Goyal, Chandan Karfa, Anupam Chattopadhyay
Why Neural Structural Obfuscation Can't Kill White-Box Watermarks for Good!
Neural Structural Obfuscation (NSO) (USENIX Security'23) is a family of ``zero cost'' structure-editing transforms (\texttt{nso\_zero}, \texttt{nso\_clique}, \texttt{nso\_split}) that inject dummy ...
Yanna Jiang, Guangsheng Yu, Qingyuan Yu, Yi Chen, Qin Wang
Testing the AdS/CFT Correspondence Through Thermodynamic Geometry of Nonlinear Electrodynamics AdS Black Holes with Generalized Entropies
We investigate the thermodynamics and thermodynamic geometry of several Anti--de Sitter black hole solutions arising from nonlinear electromagnetic theories, namely the ModMax, nonlinear electrodyn...
Abhishek Baruah, Amijit Bhattacharjee, Prabwal Jyoti Phukon
Disentangled Latent Dynamics Manifold Fusion for Solving Parameterized PDEs
Generalizing neural surrogate models across different PDE parameters remains difficult because changes in PDE coefficients often make learning harder and optimization less stable. The problem becom...
Zhangyong Liang, Ji Zhang
Multivariate normality test based on the uniform distribution on the Stiefel manifold
This study presents a new procedure for necessary tests of multivariate normality based on the uniform distribution on the Stiefel manifold. We demonstrate that the test statistic, which is formed ...
Koki Shimizu, Toshiya Iwashita
Vision Verification Enhanced Fusion of VLMs for Efficient Visual Reasoning
With the growing number and diversity of Vision-Language Models (VLMs), many works explore language-based ensemble, collaboration, and routing techniques across multiple VLMs to improve multi-model...
Selim Furkan Tekin, Yichang Xu, Gaowen Liu, Ramana Rao Kompella, Margaret L. Loper, Ling Liu
VFM-Recon: Unlocking Cross-Domain Scene-Level Neural Reconstruction with Scale-Aligned Foundation Priors
Scene-level neural volumetric reconstruction from monocular videos remains challenging, especially under severe domain shifts. Although recent advances in vision foundation models (VFMs) provide tr...
Yuhang Ming, Tingkang Xi, Xingrui Yang, Lixin Yang, Yong Peng, Cewu Lu, Wanzeng Kong
Beyond the Merger-Quasar-Quench Paradigm I: Mergers are neither necessary nor sufficient to quench central galaxies in IllustrisTNG
The cessation of star formation in galaxies, known as 'quenching', is a complex, multi-scale process which has been theorized to be linked to galaxy mergers. In this paper, we investigate the poten...
Camilo A. Casimiro, Asa F. L. Bluck, Paul Goubert, Thomas Pinto Franco, Joanna M. Piotrowska
ExpanderGraph-128: A Novel Graph-Theoretic Block Cipher with Formal Security Analysis and Hardware Implementation
Lightweight block cipher design has largely focused on incremental optimization of established paradigms such as substitution--permutation networks, Feistel structures, and ARX constructions, where...
W. A. Susantha Wijesinghe
Weakly Time-Coupled Approximation of Markov Decision Processes
Finite-horizon Markov decision processes (MDPs) with high-dimensional exogenous uncertainty and endogenous states arise in operations and finance, including the valuation and exercise of Bermudan a...
Negar Soheili, Selvaprabu Nadarajah, Bo Yang
Adversarial Stress Tests for Quantum Certification
We develop a practical framework for semi-device-independent (SDI) certification under operational deviations from the ideal protocol model. Apparent violations of classical benchmarks need not sig...
Veronica Sanz, Augusto Smerzi
When Drafts Evolve: Speculative Decoding Meets Online Learning
Speculative decoding has emerged as a widely adopted paradigm for accelerating large language model inference, where a lightweight draft model rapidly generates candidate tokens that are then verif...
Yu-Yang Qian, Hao-Cong Wu, Yichao Fu, Hao Zhang, Peng Zhao
Early Pruning for Public Transport Routing
Routing algorithms for public transport, particularly the widely used RAPTOR and its variants, often face performance bottlenecks during the transfer relaxation phase, especially on dense transfer ...
Andrii Rohovyi, Abdallah Abuaisha, Toby Walsh
Pointwise mutual information bounded by stochastic Fisher information
We derive general upper bounds to pointwise mutual information in terms of stochastic Fisher information and show these bounds average to known results in the literature for bounds to mutual inform...
Pedro B. Melo
Hot Jupiter - Cold Jupiter: A complex sibling relation
A handful of planetary systems hosting a Hot Jupiter have been subsequently found to also host long-period giant planets. These ``cold Jupiters,'' giant planets residing beyond the snow line ($\sim...
Adriana Errico, Robert A. Wittenmyer, Jonathan Horner, Brad Carter, Valeria López
Consistent and powerful CUSUM change-point test for panel data with changes in variance
This paper investigates change-point of variance in panel data models with time series of $α$-mixing. Based on the cumulative sum (CUSUM) method and the individual differences, we construct a CUSUM...
Wenzhi Yang, Yueting Xu, Xiaoping Shi, Qiong Li
Trajectory probing of complex-frequency scattering with chirped analytic pulses
Characterizing resonant scatterers is challenging because their poles and zeros usually lie away from the real-frequency axis, whereas most measurements sample only real frequencies and infer off-a...
Alex Krasnok, Denis Seletskiy
Gaussian and bootstrap approximations for functional principal component regression
Asymptotic inference using functional principal component regression (FPCR) has long been considered difficult, largely because, upon any scalar scaling, the FPCR estimator fails to satisfy a centr...
Hyemin Yeon