Papers
Research papers from arXiv and related sources
IOSVLM: A 3D Vision-Language Model for Unified Dental Diagnosis from Intraoral Scans
3D intraoral scans (IOS) are increasingly adopted in routine dentistry due to abundant geometric evidence, and unified multi-disease diagnosis is desirable for clinical documentation and communicat...
Huimin Xiong, Zijie Meng, Tianxiang Hu, Chenyi Zhou, Yang Feng, Zuozhu Liu
Anticipatory Planning for Multimodal AI Agents
Recent advances in multimodal agents have improved computer-use interaction and tool-usage, yet most existing systems remain reactive, optimizing actions in isolation without reasoning about future...
Yongyuan Liang, Shijie Zhou, Yu Gu, Hao Tan, Gang Wu, Franck Dernoncourt, Jihyung Kil, Ryan A. Ro...
SOMP: Scalable Gradient Inversion for Large Language Models via Subspace-Guided Orthogonal Matching Pursuit
Gradient inversion attacks reveal that private training text can be reconstructed from shared gradients, posing a privacy risk to large language models (LLMs). While prior methods perform well in s...
Yibo Li, Qiongxiu Li
Finding Common Ground in a Sea of Alternatives
We study the problem of selecting a statement that finds common ground across diverse population preferences. Generative AI is uniquely suited for this task because it can access a practically infi...
Jay Chooi, Paul Gölz, Ariel D. Procaccia, Benjamin Schiffer, Shirley Zhang
Probing Cultural Signals in Large Language Models through Author Profiling
Large language models (LLMs) are increasingly deployed in applications with societal impact, raising concerns about the cultural biases they encode. We probe these representations by evaluating whe...
Valentin Lafargue, Ariel Guerra-Adames, Emmanuelle Claeys, Elouan Vuichard, Jean-Michel Loubes
Nonstandard Errors in AI Agents
We study whether state-of-the-art AI coding agents, given the same data and research question, produce the same empirical results. Deploying 150 autonomous Claude Code agents to independently test ...
Ruijiang Gao, Steven Chong Xiao
When the City Teaches the Car: Label-Free 3D Perception from Infrastructure
Building robust 3D perception for self-driving still relies heavily on large-scale data collection and manual annotation, yet this paradigm becomes impractical as deployment expands across diverse ...
Zhen Xu, Jinsu Yoo, Cristian Bautista, Zanming Huang, Tai-Yu Pan, Zhenzhen Liu, Katie Z Luo, Mark...
Bayesian Inference of Psychometric Variables From Brain and Behavior in Implicit Association Tests
Objective. We establish a principled method for inferring mental health related psychometric variables from neural and behavioral data using the Implicit Association Test (IAT) as the data generati...
Christian A. Kothe, Sean Mullen, Michael V. Bronstein, Grant Hanada, Marcelo Cicconet, Aaron N. M...
Prospects for precision CE$ν$NS measurements with electron-capture neutrinos and lithium-based bolometers
We evaluate the feasibility of high-precision coherent elastic neutrino-nucleus scattering measurements exploiting mono-energetic neutrinos produced by electron-capture (EC) decays of intense radio...
Giovanni Benato, Francesca M. Pofi, Andrei Puiu, Christoph A. Ternes
Ember: A Serverless Peer-to-Peer End-to-End Encrypted Messaging System over an IPv6 Mesh Network
This paper presents Ember, a serverless peer-to-peer messaging system providing end-to-end encrypted communication over a decentralised IPv6 mesh network. Ember operates without central servers, en...
Hamish Alsop, Leandros Maglaras, Naghmeh Moradpoor
Differential Harm Propensity in Personalized LLM Agents: The Curious Case of Mental Health Disclosure
Large language models (LLMs) are increasingly deployed as tool-using agents, shifting safety concerns from harmful text generation to harmful task completion. Deployed systems often condition on us...
Caglar Yildirim
IQuest-Coder-V1 Technical Report
In this report, we introduce the IQuest-Coder-V1 series-(7B/14B/40B/40B-Loop), a new family of code large language models (LLMs). Moving beyond static code representations, we propose the code-flow...
Jian Yang, Wei Zhang, Shawn Guo, Zhengmao Ye, Lin Jing, Shark Liu, Yizhi Li, Jiajun Wu, Cening Li...
Understanding Quantization of Optimizer States in LLM Pre-training: Dynamics of State Staleness and Effectiveness of State Resets
Quantizing optimizer states is becoming an important ingredient of memory-efficient large-scale pre-training, but the resulting optimizer dynamics remain only partially understood. We study low-pre...
Kristi Topollai, Anna Choromanska
The Cost of Reasoning: Chain-of-Thought Induces Overconfidence in Vision-Language Models
Vision-language models (VLMs) are increasingly deployed in high-stakes settings where reliable uncertainty quantification (UQ) is as important as predictive accuracy. Extended reasoning via chain-o...
Robert Welch, Emir Konuk, Kevin Smith
Emotion-Aware Classroom Quality Assessment Leveraging IoT-Based Real-Time Student Monitoring
This study presents high-throughput, real-time multi-agent affective computing framework designed to enhance classroom learning through emotional state monitoring. As large classroom sizes and limi...
Hai Nguyen, Hieu Dao, Hung Nguyen, Nam Vu, Cong Tran
Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models
Large language models (LLMs) perform strongly on many NLP tasks, but their ability to produce explicit linguistic structure remains unclear. We evaluate instruction-tuned LLMs on two structured pre...
Mohamed Adel, Bashar Alhafni, Nizar Habash
Novelty-Driven Target-Space Discovery in Automated Electron and Scanning Probe Microscopy
Modern automated microscopy faces a fundamental discovery challenge: in many systems, the most important scientific information does not reside in the immediately visible image features, but in the...
Utkarsh Pratiush, Kamyar Barakati, Boris N. Slautin, Catherine C. Bodinger, Christopher D. Lowe, ...
Design of Transit Networks: Global Optimization of Continuous Approximation Models via Geometric Programming
Continuous approximation (CA) models have been widely adopted in transit network design studies due to their strong analytical tractability and high computational efficiency. However, such models a...
Haoyang Mao, Weihua Gu, Wenbo Fan, Zhicheng Jin, Xiaokuan Zhao
A Variational Pseudo-Observation Guided Nudged Particle Filter
Nonlinear filtering with standard PF methods requires mitigative techniques to quell weight degeneracy, such as resampling. This is especially true in high-dimensional systems with sparse observati...
Theofania Karampela, Ryne Beeson
A Compact Broadband Purcell Filter for Superconducting Quantum Circuits in a 3D Flip-Chip Architecture
Fast and high-fidelity qubit readout requires strong coupling between the readout resonator and the feedline. However, such coupling unavoidably enhances qubit decay through the Purcell effect. We ...
Zhen Luo, Lea Richard, Ivan Tsitsilin, Anirban Bhattacharjee, Christian M. F. Schneider, Stefan F...