Tootfinder

Therapeutic AI and the Hidden Risks of Over-Disclosure: An Embedded AI-Literacy Framework for Mental Health Privacy
Soraya S. Anvari, Rina R. Wehbe
https://arxiv.org/abs/2510.10805

Therapeutic AI and the Hidden Risks of Over-Disclosure: An Embedded AI-Literacy Framework for Mental Health Privacy
Large Language Models (LLMs) are increasingly deployed in mental health contexts, from structured therapeutic support tools to informal chat-based well-being assistants. While these systems increase accessibility, scalability, and personalization, their integration into mental health care brings privacy and safety challenges that have not been well-examined. Unlike traditional clinical interactions, LLM-mediated therapy often lacks a clear structure for what information is collected, how it is …

Privacy startup Duality says it has developed a private LLM inference framework that uses fully homomorphic encryption to let LLMs answer encrypted prompts (Rina Diane Caballar/IEEE Spectrum)
https://spectrum.ieee.org/homomorphic-encryption-llm

Homomorphic Encryption LLM Secures AI Chats
Can your chatbot keep secrets? Discover how Duality's tech is changing the privacy game for AI conversations.

Predictive inference for time series: why is split conformal effective despite temporal dependence?
Rina Foygel Barber, Ashwin Pananjady
https://arxiv.org/abs/2510.02471 https:/…

Predictive inference for time series: why is split conformal effective despite temporal dependence?
We consider the problem of uncertainty quantification for prediction in a time series: if we use past data to forecast the next time point, can we provide valid prediction intervals around our forecasts? To avoid placing distributional assumptions on the data, in recent years the conformal prediction method has been a popular approach for predictive inference, since it provides distribution-free coverage for any iid or exchangeable data distribution. However, in the time series setting, the str…

Replaced article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Hoeffding and Bernstein inequalities for weighted sums of exchangeable random variables
Rina Foygel Barber

High energy emission powered by accreting companions of Be/gamma Cas stars
Rina G. Rast, Yael Naze, Jonathan Labadie-Bartz, Carol E. Jones, Christiana Erba, Ken Gayley, Asif ud-Doula, Coralie Neiner, Jeremy J. Drake
https://arxiv.org/abs/2510.00891

High energy emission powered by accreting companions of Be/gamma Cas stars
The origin of the hard, bright X-ray emission that defines the gamma Cas analog class of Be stars remains an outstanding question in Be star literature. This work explores the possibility that the X-ray flux is produced by accretion onto a white dwarf companion. We use three-dimensional smoothed particle hydrodynamics simulations to model the prototype gamma Cas system assuming a white dwarf companion and investigate the accretion of the circumstellar material by the secondary star. We contrast…

Replaced article(s) found for cs.RO. https://arxiv.org/list/cs.RO/new
[2/2]:
- Spatial Language Likelihood Grounding Network for Bayesian Fusion of Human-Robot Observations
Supawich Sitdhipol, Waritwong Sukprasongdee, Ekapol Chuangsuwanich, Rina Tse

Max-Min and 1-Bounded Space Algorithms for the Bin Packing Problem
Hiroshi Fujiwara, Rina Atsumi, Hiroaki Yamamoto
https://arxiv.org/abs/2508.18718 https://

Max-Min and 1-Bounded Space Algorithms for the Bin Packing Problem
In the (1-dimensional) bin packing problem, we are asked to pack all the given items into bins, each of capacity one, so that the number of non-empty bins is minimized. Zhu~[Chaos, Solitons \& Fractals 2016] proposed an approximation algorithm $MM$ that sorts the item sequence in a non-increasing order by size at the beginning, and then repeatedly packs, into the current single open bin, first as many of the largest items in the remaining sequence as possible and then as many of the smallest it…

Binaural Unmasking in Practical Use: Perceived Level of Phase-inverted Speech in Environmental Noise
Rina Kotani, Chiaki Miyazaki, Shiro Suzuki
https://arxiv.org/abs/2509.01929 …

Binaural Unmasking in Practical Use: Perceived Level of Phase-inverted Speech in Environmental Noise
We aim to develop a technology that makes the sound from earphones and headphones easier to hear without increasing the sound pressure or eliminating ambient noise. To this end, we focus on harnessing the phenomenon of binaural unmasking through phase reversal in one ear. Specifically, we conduct experiments to evaluate the improvement of audibility caused by the phenomenon, using conditions that approximate practical scenarios. We use speech sounds by various speakers, including women, and noi…

Replaced article(s) found for math.AG. https://arxiv.org/list/math.AG/new
[1/1]:
- $\mathbb{P}^n$-functors
Rina Anno, Timothy Logvinenko
https://

Spatial Language Likelihood Grounding Network for Bayesian Fusion of Human-Robot Observations
Supawich Sitdhipol, Waritwong Sukprasongdee, Ekapol Chuangsuwanich, Rina Tse
https://arxiv.org/abs/2507.19947

Spatial Language Likelihood Grounding Network for Bayesian Fusion of Human-Robot Observations
Fusing information from human observations can help robots overcome sensing limitations in collaborative tasks. However, an uncertainty-aware fusion framework requires a grounded likelihood representing the uncertainty of human inputs. This paper presents a Feature Pyramid Likelihood Grounding Network (FP-LGN) that grounds spatial language by learning relevant map image features and their relationships with spatial relation semantics. The model is trained as a probability estimator to capture a…

Replaced article(s) found for cond-mat.str-el. https://arxiv.org/list/cond-mat.str-el/new
[1/1]:
- Photoinduced non-reciprocal magnetism
Ryo Hanai, Daiki Ootsuki, Rina Tazai

Efficiency of viscous angular momentum transport in dissipating Be binaries
Peter Quigley, Carol E. Jones, Kenneth Gayley, Anahi Granada, Stan Owocki, Rina Rast, Mark Suffak, Atsuo T. Okazaki, Asif ud-Doula, Ji\v{r}\'i Krti\v{c}ka, Alex C. Carciofi, Jeremy J. Drake
https://arxiv.org/abs/2509.19468

Efficiency of viscous angular momentum transport in dissipating Be binaries
Angular momentum transport is a fundamental process shaping the structure, evolution, and lifespans of stars and disks across a wide range of astrophysical systems. Be stars offer a valuable environment for studying viscous transport of angular momentum in massive stars, thanks to their rapid rotation, observable decretion disks, and likely absence of strong magnetic fields. This study analyzes angular momentum loss in 40 Be binary simulations spanning a range of orbital separations and compani…

False discovery rate control with compound p-values
Rina Foygel Barber, Richard J Samworth
https://arxiv.org/abs/2507.21465 https://arxiv.org/pdf/2507.2146…

False discovery rate control with compound p-values
In the setting of multiple testing, compound p-values generalize p-values by asking for superuniformity to hold only \emph{on average} across all true nulls. We study the properties of the Benjamini--Hochberg procedure applied to compound p-values. Under independence, we show that the false discovery rate (FDR) is at most $1.93α$, where $α$ is the nominal level, and exhibit a distribution for which the FDR is $\frac{7}{6}α$. If additionally all nulls are true, then the upper bound can be imp…