Tootfinder

PromptLocate: Localizing Prompt Injection Attacks
Yuqi Jia, Yupei Liu, Zedian Shao, Jinyuan Jia, Neil Gong
https://arxiv.org/abs/2510.12252 https://arxiv.o…

PromptLocate: Localizing Prompt Injection Attacks
Prompt injection attacks deceive a large language model into completing an attacker-specified task instead of its intended task by contaminating its input data with an injected prompt, which consists of injected instruction(s) and data. Localizing the injected prompt within contaminated data is crucial for post-attack forensic analysis and data recovery. Despite its growing importance, prompt injection localization remains largely unexplored. In this work, we bridge this gap by proposing Prompt…

Position: AI Will Transform Neuropsychology Through Mental Health Digital Twins for Dynamic Mental Health Care, Especially for ADHD
Neil Natarajan, Sruthi Viswanathan, Xavier Roberts-Gaal, Michelle Marie Martel
https://arxiv.org/abs/2510.07409

Position: AI Will Transform Neuropsychology Through Mental Health Digital Twins for Dynamic Mental Health Care, Especially for ADHD
Static solutions don't serve a dynamic mind. Thus, we advocate a shift from static mental health diagnostic assessments to continuous, artificial intelligence (AI)-driven assessment. Focusing on Attention-Deficit/Hyperactivity Disorder (ADHD) as a case study, we explore how generative AI has the potential to address current capacity constraints in neuropsychology, potentially enabling more personalized and longitudinal care pathways. In particular, AI can efficiently conduct frequent, low-level…

NaviGait: Navigating Dynamically Feasible Gait Libraries using Deep Reinforcement Learning
Neil C. Janwani, Varun Madabushi, Maegan Tucker
https://arxiv.org/abs/2510.11542 https…

NaviGait: Navigating Dynamically Feasible Gait Libraries using Deep Reinforcement Learning
Reinforcement learning (RL) has emerged as a powerful method to learn robust control policies for bipedal locomotion. Yet, it can be difficult to tune desired robot behaviors due to unintuitive and complex reward design. In comparison, offline trajectory optimization methods, like Hybrid Zero Dynamics, offer more tuneable, interpretable, and mathematically grounded motion plans for high-dimensional legged systems. However, these methods often remain brittle to real-world disturbances like exter…

Bias-Aware AI Chatbot for Engineering Advising at the University of Maryland A. James Clark School of Engineering
Prarthana P. Kartholy, Thandi M. Labor, Neil N. Panchal, Sean H. Wang, Hillary N. Owusu
https://arxiv.org/abs/2510.09636

Bias-Aware AI Chatbot for Engineering Advising at the University of Maryland A. James Clark School of Engineering
Selecting a college major is a difficult decision for many incoming freshmen. Traditional academic advising is often hindered by long wait times, intimidating environments, and limited personalization. AI Chatbots present an opportunity to address these challenges. However, AI systems also have the potential to generate biased responses, prejudices related to race, gender, socioeconomic status, and disability. These biases risk turning away potential students and undermining reliability of AI s…

Near the Runaway: The Climate and Habitability of Teegarden's Star b
Ryan Boukrouche, Rodrigo Caballero, Neil Lewis
https://arxiv.org/abs/2510.11940 https://

Near the Runaway: The Climate and Habitability of Teegarden's Star b
Teegarden's Star b, a nearby terrestrial world receiving an Earth-like instellation, is a prime candidate for next-generation observatories targeting temperate exoplanets in their habitable zones. We employ a suite of three-dimensional global climate model (GCM) simulations to (1) map the inner boundary of the habitable zone of Teegarden's Star b and (2) characterize its surface climate under the assumption of an Earth-analog atmosphere. Our simulations show that, with its most recently estimat…

Inoculation Prompting: Instructing LLMs to misbehave at train-time improves test-time alignment
Nevan Wichers, Aram Ebtekar, Ariana Azarbal, Victor Gillioz, Christine Ye, Emil Ryd, Neil Rathi, Henry Sleight, Alex Mallen, Fabien Roger, Samuel Marks
https://arxiv.org/abs/2510.05024

Inoculation Prompting: Instructing LLMs to misbehave at train-time improves test-time alignment
Large language models are sometimes trained with imperfect oversight signals, leading to undesired behaviors such as reward hacking and sycophancy. Improving oversight quality can be expensive or infeasible, motivating methods that improve learned behavior despite an imperfect training signal. We introduce Inoculation Prompting (IP), a simple but counterintuitive technique that prevents learning of an undesired behavior by modifying training prompts to explicitly request it. For example, to ino…

BlackIce: A Containerized Red Teaming Toolkit for AI Security Testing
Caelin Kaplan, Alexander Warnecke, Neil Archibald
https://arxiv.org/abs/2510.11823 https://

BlackIce: A Containerized Red Teaming Toolkit for AI Security Testing
AI models are being increasingly integrated into real-world systems, raising significant concerns about their safety and security. Consequently, AI red teaming has become essential for organizations to proactively identify and address vulnerabilities before they can be exploited by adversaries. While numerous AI red teaming tools currently exist, practitioners face challenges in selecting the most appropriate tools from a rapidly expanding landscape, as well as managing complex and frequently c…

Who Do You Think You Are? Creating RSE Personas from GitHub Interactions
Felicity Anderson, Julien Sindt, Neil Chue Hong
https://arxiv.org/abs/2510.05390 https://

Who Do You Think You Are? Creating RSE Personas from GitHub Interactions
We describe data-driven RSE personas: an approach combining software repository mining and data-driven personas applied to research software (RS), an attempt to describe and identify common and rare patterns of Research Software Engineering (RSE) development. This allows individuals and RS project teams to understand their contributions, impact and repository dynamics - an important foundation for improving RSE. We evaluate the method on different patterns of collaborative interaction behaviour…

kabr-tools: Automated Framework for Multi-Species Behavioral Monitoring
Jenna Kline, Maksim Kholiavchenko, Samuel Stevens, Nina van Tiel, Alison Zhong, Namrata Banerji, Alec Sheets, Sowbaranika Balasubramaniam, Isla Duporge, Matthew Thompson, Elizabeth Campolongo, Jackson Miliko, Neil Rosser, Tanya Berger-Wolf, Charles V. Stewart, Daniel I. Rubenstein
https://

kabr-tools: Automated Framework for Multi-Species Behavioral Monitoring
A comprehensive understanding of animal behavior ecology depends on scalable approaches to quantify and interpret complex, multidimensional behavioral patterns. Traditional field observations are often limited in scope, time-consuming, and labor-intensive, hindering the assessment of behavioral responses across landscapes. To address this, we present kabr-tools (Kenyan Animal Behavior Recognition Tools), an open-source package for automated multi-species behavioral monitoring. This framework in…

From X-rays to High-Energy Gamma-rays: A Comprehensive Multi-Wavelength Study of Early Gamma-Ray Burst Afterglows
P. Tiwari, B. Banerjee, D. Miceli, G. Oganesyan, A. Ierardi, S. Macera, M. Branchesi, L. Nava, S. Mohnani, S. Agarwal, A. Shukla
https://arxiv.org/abs/2510.05239

From X-rays to High-Energy Gamma-rays: A Comprehensive Multi-Wavelength Study of Early Gamma-Ray Burst Afterglows
Gamma-ray Bursts (GRBs) generate powerful relativistic jets that inject a large amount of energy into their surrounding environment, producing blast waves that accelerate particles to high energies. The GRB afterglow radiation provides a powerful means to investigate the microphysics of relativistic shocks and to probe the medium surrounding the progenitor of the burst. In this study, we present a comprehensive multiwavelength analysis of 31 GRBs observed between 2008 and 2024 from the Neil Geh…

Lithographic integration of TES microcalorimeters with SQUID multiplexer circuits for large format spectrometers
Robinjeet Singh, Avirup Roy, Daniel Becker, Johnathan D. Gard, Mark W. Keller, John A. B. Mates, Kelsey M. Morgan, Nathan J. Ortiz, Daniel R. Schmidt, Daniel S. Swetz, Joel N. Ullom, Leila R. Vale, Michael Vissers, Galen C. O'Neil, Joel C. Weber
…

Lithographic integration of TES microcalorimeters with SQUID multiplexer circuits for large format spectrometers
Arrays of hundreds or thousands of low temperature detectors have been deployed for many experiments, both bolometers for long wavelength applications and calorimeters for shorter wavelength applications. One challenge that is common to many of these arrays is the efficient use of focal plane area to achieve a large fill fraction of absorbers coupled to detectors. We are developing an integrated fabrication of soft X-ray transition edge sensors (TES) and microwave SQUID multiplexers ($μ$MUX) w…

Replaced article(s) found for hep-ph. https://arxiv.org/list/hep-ph/new
[1/2]:
- Repurposing lattice QCD results for composite phenomenology
Thomas DeGrand, Ethan T. Neil

The two conduction bands of monolayer CrSBr on Au
Yogal Prasad Ghimirey, Laxman Nagireddy, Cephise Cacho, Neil R. Wilson, Matthew D. Watson
https://arxiv.org/abs/2510.04925 http…

The two conduction bands of monolayer CrSBr on Au
We report the electronic structure of monolayer CrSBr exfoliated onto mica template-stripped gold substrates. Angle-resolved photoemission spectroscopy reveals charge transfer from the substrate, populating the conduction band of monolayer CrSBr, accompanied by a pronounced reduction in the quasiparticle band gap. Furthermore, we observe two separate conduction bands that exhibit a splitting at the X point. This indicates a breaking of glide-mirror symmetry, which in the bulk or in a free-stand…

Self-interacting dark matter in the center of a Local Group dwarf galaxy and its satellites
Thales A. Gutcke, Giulia Despali, Stephanie O'Neil, Mark Vogelsberger, Azadeh Fattahi, David B. Sanders
https://arxiv.org/abs/2510.05258

Self-interacting dark matter in the center of a Local Group dwarf galaxy and its satellites
We present a detailed comparison of a Local Group dwarf galaxy analogue evolved in two cosmological models: the standard $Λ$CDM and a self-interacting dark matter (SIDM) model with a velocity-dependent cross-section. Both simulations are run with the high-resolution, hydrodynamical LYRA galaxy formation model, allowing us to explore the global and substructure properties of the dwarf in a consistent context. While the overall halo growth, final mass, and subhalo mass functions remain largely u…

Replaced article(s) found for econ.EM. https://arxiv.org/list/econ.EM/new
[1/1]:
- Counting Defiers: A Design-Based Model of an Experiment Can Reveal Evidence Beyond the Average Ef...
Neil Christy, Amanda Ellen Kowalski

GW250114 reveals black hole horizon signatures
Neil Lu, Sizheng Ma, Ornella J. Piccinni, Yanbei Chen, Ling Sun
https://arxiv.org/abs/2510.01001 https://arx…

GW250114 reveals black hole horizon signatures
The horizon of a black hole, the "surface of no return," is characterized by its rotation frequency $Ω_H$ and surface gravity $κ$. A striking signature is that any infalling object appears to orbit at $Ω_H$ due to frame dragging, while its emitted signals decay exponentially at a rate set by $κ$ as a consequence of gravitational redshift. Recent theoretical work predicts that the merger phase of gravitational waves from binary black hole coalescences carries direct imprints of the remnant h…

Optical Design Pathways to Fluidic Space-Assembled Reflectors & Dual-Configuration Spectrographs for Characterizing Exo-Earths
Enrico Biancalani, Edward Balaban, Ruslan Belikov, Eduardo Bendek, Valeri Frumkin, Israel Gabay, Guangjun Gao, Qian Gong, Christine Gregg, Tyler Groff, Joseph Howard, Omer Luria, Michael McElwain, Lee Mundy, Rachel Ticknor, Sylvain Veilleux, Neil Zimmerman

Optical Design Pathways to Fluidic Space-Assembled Reflectors & Dual-Configuration Spectrographs for Characterizing Exo-Earths
$\textbf{Fluidic Telescopes}$ | We present a conceptual framework for optically designing space-assembled telescopes whose primary mirror is formed $\textit{in situ}$ via the enabling, scale-invariant technology of fluidic shaping. In-space assembly of optical reflectors can solve light-gathering aperture scaling, which currently limits space-borne optical telescopes. Our compass reduces the top-level optical design trade to three types of avenues -- a fluidic pathway, a legacy one buildin…

Mitigating Modal Imbalance in Multimodal Reasoning
Chen Henry Wu, Neil Kale, Aditi Raghunathan
https://arxiv.org/abs/2510.02608 https://arxiv.org/pdf/2510.…

Mitigating Modal Imbalance in Multimodal Reasoning
Foundation models (FMs) deployed in real-world tasks such as computer-use agents must integrate diverse modalities. How good are FMs at performing joint reasoning, simultaneously reasoning over multiple modalities, especially when the modalities interact and relate to each other to form cross-modal context? To better understand this problem, we study FMs on cross-modal conflicts: scenarios where conflicting evidence is presented across modalities. This allows us to examine whether FMs prioritiz…

A Possibility Frontier Approach to Diverse Talent Selection
Neil Natarajan, Kadeem Noray
https://arxiv.org/abs/2510.06119 https://arxiv.org/pdf/2510.06119

A Possibility Frontier Approach to Diverse Talent Selection
Organizations (e.g., talent investment programs, schools, firms) are perennially interested in selecting cohorts of talented people. And organizations are increasingly interested in selecting diverse cohorts. Except in trivial cases, measuring the tradeoff between cohort diversity and talent is computationally difficult. Thus, organizations are presently unable to make Pareto-efficient decisions about these tradeoffs. We introduce an algorithm that approximates upper bounds on cohort talent and…

Numerical modeling of laser cooling in molecules: From simple diatomics to polyatomics and radioactive species
Felix Kogel, Tatsam Garg, Phillip Gro{\ss}, Lukas Leczek, Marian Rockenh\"auser, Neil Shah, Jakob Wei{\ss}, Andreas Schindewolf, Tim Langen
https://arxiv.org/abs/2510.16203

Markov Decision Processing Networks
Sanidhay Bhambay, Thirupathaiah Vasantam, Neil Walton
https://arxiv.org/abs/2509.24541 https://arxiv.org/pdf/2509.24541…

Markov Decision Processing Networks
We introduce Markov Decision Processing Networks (MDPNs) as a multiclass queueing network model where service is a controlled, finite-state Markov process. The model exhibits a decision-dependent service process where actions taken influence future service availability. Viewed as a two-sided queueing model, this captures settings such as assemble-to-order systems, ride-hailing platforms, cross-skilled call centers, and quantum switches. We first characterize the capacity region of MDPNs. Unli…

Multihead Finite-State Dimension
Xiang Huang, Xiaoyuan Li, Jack H. Lutz, Neil Lutz
https://arxiv.org/abs/2509.22912 https://arxiv.org/pdf/2509.22912…

Multihead Finite-State Dimension
We introduce multihead finite-state dimension, a generalization of finite-state dimension in which a group of finite-state agents (the heads) with oblivious, one-way movement rules, each reporting only one symbol at a time, enable their leader to bet on subsequent symbols in an infinite data stream. In aggregate, such a scheme constitutes an $h$-head finite state gambler whose maximum achievable growth rate of capital in this task, quantified using betting strategies called gales, determines th…

Ecosystem Recovery to Historical Targets Becomes Unattainable Under Modelled Fishing and Climate in the Barents Sea
Matthew Hatton, Jack H Laverick, Neil Banas, Michael Heath
https://arxiv.org/abs/2510.04806

Ecosystem Recovery to Historical Targets Becomes Unattainable Under Modelled Fishing and Climate in the Barents Sea
Climate change and fisheries jointly shape the resilience of the Barents Sea marine ecosystem, yet the recovery of key fish populations to climate and anthropogenic disturbances requires further investigation. This study examines how fishing pressure and climate change, driven by the NEMO-MEDUSA Earth system model, influence the recovery times of Demersal and Planktivorous fish in the Barents Sea. We used the StrathE2EPolar end-to-end ecosystem model to simulate transient dynamics under increas…

EditTrack: Detecting and Attributing AI-assisted Image Editing
Zhengyuan Jiang, Yuyang Zhang, Moyang Guo, Neil Zhenqiang Gong
https://arxiv.org/abs/2510.01173 https://

EditTrack: Detecting and Attributing AI-assisted Image Editing
In this work, we formulate and study the problem of image-editing detection and attribution: given a base image and a suspicious image, detection seeks to determine whether the suspicious image was derived from the base image using an AI editing model, while attribution further identifies the specific editing model responsible. Existing methods for detecting and attributing AI-generated images are insufficient for this problem, as they focus on determining whether an image was AI-generated/edit…

Spectral-temporal processing using integrated recursive electro-optic circuit
Xudong Li, Yaowen Hu, Tong Ge, Andrea Cordaro, Yunxiang Song, Xinrui Zhu, Shengyuan Lu, Keith Powell, Let\'icia Magalh\~aes, Urban Senica, Neil Sinclair, Marko Lon\v{c}ar
https://arxiv.org/abs/2509.25102

Spectral-temporal processing using integrated recursive electro-optic circuit
Advances in integrated photonics have enabled unprecedented level of control of light, powering a wide range of photonic technologies from communications and computing to precision metrology and quantum information. However, the conventional on-chip optical signal processing approaches based on optical waveguides and cavities suffer from their large physical footprint and narrow operating bandwidth, respectively. To address this, we propose and experimentally demonstrate, using the thin film li…

Chromaticity of stellar activity in radial velocities : Anti-correlated families of lines on the M dwarf EV Lac with SPIRou and SOPHIE
Pierre Larue, Xavier Delfosse, Andres Carmona, Nad\`ege Meunier, \'Etienne Artigau, Stefano Bellotti, Paul Charpentier, Claire Moutou, Jean-Fran\c{c}ois Donati, Isabelle Boisse, Thierry Forveille, Luc Arnold, Vincent Bourrier, Xavier Bonfils, Charles Cadieux, Antoine Chomez, Neil Cook, Pia Cortes Zuleta, Paul Cristofari, Rodrigo Diaz, Ren\'e Doy…

Chromaticity of stellar activity in radial velocities : Anti-correlated families of lines on the M dwarf EV Lac with SPIRou and SOPHIE
Context. In the search for exoplanets using radial velocities (RV), stellar activity has become one of the main limiting factors for detectability. Fortunately, activity-induced RV signals are wavelength-dependent or chromatic, unlike planetary signals. This study exploits the broad spectral coverage provided by the combined use of SOPHIE and SPIRou velocimeters to investigate the chromatic nature of the activity signal of the highly active M dwarf EV Lac. Aims. We aim to understand the origi…

WAInjectBench: Benchmarking Prompt Injection Detections for Web Agents
Yinuo Liu, Ruohan Xu, Xilong Wang, Yuqi Jia, Neil Zhenqiang Gong
https://arxiv.org/abs/2510.01354 https://…

WAInjectBench: Benchmarking Prompt Injection Detections for Web Agents
Multiple prompt injection attacks have been proposed against web agents. At the same time, various methods have been developed to detect general prompt injection attacks, but none have been systematically evaluated for web agents. In this work, we bridge this gap by presenting the first comprehensive benchmark study on detecting prompt injection attacks targeting web agents. We begin by introducing a fine-grained categorization of such attacks based on the threat model. We then construct datase…

Crosslisted article(s) found for cs.MA. https://arxiv.org/list/cs.MA/new
[1/1]:
- ORCA: Agentic Reasoning For Hallucination and Adversarial Robustness in Vision-Language Models
Chung-En Johnny Yu (Neil), Hsuan-Chih (Neil), Chen, Brian Jalaian, Nathaniel D. Bastian

RangeSAM: Leveraging Visual Foundation Models for Range-View repesented LiDAR segmentation
Paul Julius K\"uhn, Duc Anh Nguyen, Arjan Kuijper, Holger Graf, Dieter Fellner, Saptarshi Neil Sinha
https://arxiv.org/abs/2509.15886

RangeSAM: Leveraging Visual Foundation Models for Range-View repesented LiDAR segmentation
Point cloud segmentation is central to autonomous driving and 3D scene understanding. While voxel- and point-based methods dominate recent research due to their compatibility with deep architectures and ability to capture fine-grained geometry, they often incur high computational cost, irregular memory access, and limited real-time efficiency. In contrast, range-view methods, though relatively underexplored - can leverage mature 2D semantic segmentation techniques for fast and accurate predicti…

Comprehensive X-ray Observations of the Exceptional Ultra-long X-ray and Gamma-ray Transient GRB 250702B with Swift, NuSTAR, and Chandra: Insights from the X-ray Afterglow Properties
Brendan O'Connor, Ramandeep Gill, James DeLaunay, Jeremy Hare, Dheeraj Pasham, Eric R. Coughlin, Ananya Bandopadhyay, Akash Anumarlapudi, Paz Beniamini, Jonathan Granot, Igor Andreoni, Jonathan Carney, Michael J. Moss, Ersin G\"o\u{g}\"u\c{s}, Jamie A. Kennea, Malte Busmann, Simone Dichiara, …

Comprehensive X-ray Observations of the Exceptional Ultra-long X-ray and Gamma-ray Transient GRB 250702B with Swift, NuSTAR, and Chandra: Insights from the X-ray Afterglow Properties
GRB 250702B is an exceptional transient that produced multiple episodes of luminous gamma-ray radiation lasting for $>25$ ks, placing it among the class of ultra-long gamma-ray bursts (GRBs). However, unlike any known GRB, a soft X-ray precursor was discovered by the Einstein Probe up to 24 hours before the gamma-ray triggers. We present comprehensive X-ray observations of the transient's afterglow obtained with the Neil Gehrels Swift Observatory, the Nuclear Spectroscopic Telescope Array, and …

Fingerprinting LLMs via Prompt Injection
Yuepeng Hu, Zhengyuan Jiang, Mengyuan Li, Osama Ahmed, Zhicong Huang, Cheng Hong, Neil Gong
https://arxiv.org/abs/2509.25448 https://

Fingerprinting LLMs via Prompt Injection
Large language models (LLMs) are often modified after release through post-processing such as post-training or quantization, which makes it challenging to determine whether one model is derived from another. Existing provenance detection methods have two main limitations: (1) they embed signals into the base model before release, which is infeasible for already published models, or (2) they compare outputs across models using hand-crafted or random prompts, which are not robust to post-processi…