Papers
Research papers from arXiv and related sources
Test of a 34 GHz EOM laser frequency comb at ESPRESSO
Laser frequency combs (LFCs) are a promising technology for wavelength calibration of astronomical high-resolution spectrographs requiring utmost accuracy and stability, since they directly transla...
Tobias M. Schmidt, Ewelina Obrzud, François Bouchy, Gaspare Lo Curto, Victor Brasch, Tobias Herr,...
Actionable Recourse in Competitive Environments: A Dynamic Game of Endogenous Selection
Actionable recourse studies whether individuals can modify feasible features to overturn unfavorable outcomes produced by AI-assisted decision-support systems. However, many such systems operate in...
Ya-Ting Yang, Quanyan Zhu
Mechanistic Insights into Enhanced Alkaline Oxygen Evolution on Zn-Al Alloy Electrodes
Electrochemical water electrolysis, which produces clean energy carriers to mitigate carbon emissions, lacks suitable, low-cost electrodes for efficient oxygen evolution reaction (OER) in alkaline ...
Abdul Ahad Mamun, Rokon Uddin Mahmud, Shahin Aziz, Muhammad Shahriar Bashar, Ahmed Sharif, Muhamm...
Differential Privacy in Generative AI Agents: Analysis and Optimal Tradeoffs
Large language models (LLMs) and AI agents are increasingly integrated into enterprise systems to access internal databases and generate context-aware responses. While such integration improves pro...
Ya-Ting Yang, Quanyan Zhu
Grievance Politics vs. Policy Debates: A Cross-Platform Analysis of Conservative Discourse on Truth Social and Reddit
We present the first large-scale comparative analysis of Truth Social and the most popular conservative Reddit communities, r/Conservative, r/conservatives, and r/Republican. Using topic modeling w...
Yining Wang, Alhasan Abdellatif, Artemis Deligianni, Hannah Hok, Yusuf Mucahit Cetinkaya, Tugrulc...
$K π$ scattering as a step towards $B \to K^* \ell^+ \ell^-$ from Lattice QCD
Rare $b\to s\ell^+\ell^-$ decays provide some of the most sensitive tests of the Standard Model and require precise and systematically improvable hadronic input from lattice QCD. For the phenomenol...
Felix Erben, Matthew Black, Peter Boyle, Matteo Di Carlo, Vera Gülpers, Maxwell T. Hansen, Nelson...
Workers' Incentives and the Optimal Taxation of AI
We characterize the optimal tax policy in an economy with human manual and cognitive labor, physical capital, and artificial intelligence (AI). Extending the dynamic taxation setup of Slavik and Ya...
Jakub Growiec, Klaus Prettner, Maciej Szkróbka
A Creative Agent is Worth a 64-Token Template
Text-to-image (T2I) models have substantially improved image fidelity and prompt adherence, yet their creativity remains constrained by reliance on discrete natural language prompts. When presented...
Ruixiao Shi, Fu Feng, Yucheng Xie, Xu Yang, Jing Wang, Xin Geng
scicode-lint: Detecting Methodology Bugs in Scientific Python Code with LLM-Generated Patterns
Methodology bugs in scientific Python code produce plausible but incorrect results that traditional linters and static analysis tools cannot detect. Several research groups have built ML-specific l...
Sergey V. Samsonau
RAMP: Reinforcement Adaptive Mixed Precision Quantization for Efficient On Device LLM Inference
Post training quantization is essential for deploying large language models (LLMs) on resource constrained hardware, yet state of the art methods enforce uniform bit widths across layers, yielding ...
Arpit Singh Gautam, Saurabh Jha
AI-Assisted Goal Setting Improves Goal Progress Through Social Accountability
Helping people identify and pursue personally meaningful career goals at scale remains a key challenge in applied psychology. Career coaching can improve goal quality and attainment, but its cost a...
Michel Schimpf, Julian Voigt, Thomas Bohné
A Deterministic Ionization Algorithm for the OSIRIS Particle-in-Cell Framework
Ionization is critical in the formation and evolution of plasma dynamics; collisional ionization, in particular, is an often overlooked source of electrons when dealing with laser-plasma interactio...
Stephen DiIorio, Ricardo Fonseca, Frank Tsung, Benjamin J. Winjum, Alec G. R. Thomas
DebugLM: Learning Traceable Training Data Provenance for LLMs
Large language models (LLMs) are trained through multi-stage pipelines over heterogeneous data sources, yet developers lack a principled way to pinpoint the specific data responsible for an observe...
Wenjie Jacky Mo, Qin Liu, Xiaofei Wen, Wenxuan Zhou, Zhe Zhao, Muhao Chen
SoK: From Silicon to Netlist and Beyond $-$ Two Decades of Hardware Reverse Engineering Research
As hardware serves as the root of trust in modern computing systems, Hardware Reverse Engineering (HRE) is foundational for security assurance. In practice, HRE enables critical security applicatio...
Zehra Karadağ, Simon Klix, René Walendy, Felix Hahn, Kolja Dorschel, Julian Speith, Christof Paar...
Differential Attention-Augmented BiomedCLIP with Asymmetric Focal Optimization for Imbalanced Multi-Label Video Capsule Endoscopy Classification
This work presents a multi-label classification framework for video capsule endoscopy (VCE) that addresses the extreme class imbalance inherent in the Galar dataset through a combination of archite...
Podakanti Satyajith Chary, Nagarajan Ganapathy
Mitigating LLM Hallucinations through Domain-Grounded Tiered Retrieval
Large Language Models (LLMs) have achieved unprecedented fluency but remain susceptible to "hallucinations" - the generation of factually incorrect or ungrounded content. This limitation is particu...
Md. Asraful Haque, Aasar Mehdi, Maaz Mahboob, Tamkeen Fatima
Procedural Generation of Algorithm Discovery Tasks in Machine Learning
Automating the development of machine learning algorithms has the potential to unlock new breakthroughs. However, our ability to improve and evaluate algorithm discovery systems has thus far been l...
Alexander D. Goldie, Zilin Wang, Adrian Hayler, Deepak Nathani, Edan Toledo, Ken Thampiratwong, A...
Physics-Aware Machine Learning for Seismic and Volcanic Signal Interpretation
Modern seismic and volcanic monitoring is increasingly shaped by continuous, multi-sensor observations and by the need to extract actionable information from nonstationary, noisy wavefields. In thi...
William Thorossian
A Continuous-Variable Quantum Fourier Layer: Applications to Filtering and PDE Solving
Fourier representations play a central role in operator learning methods for partial differential equations and are increasingly being explored in quantum machine learning architectures. The classi...
Paolo Marcandelli, Stefano Mariani, Martina Siena, Stefano Markidis
Revisiting foundation models for cell instance segmentation
Cell segmentation is a fundamental task in microscopy image analysis. Several foundation models for cell segmentation have been introduced, virtually all of them are extensions of Segment Anything ...
Anwai Archit, Constantin Pape