Tootfinder

Adolfo Garcia-Sastre, a microbiologist at Mount Sinai’s medical school who wasn’t involved with the study, called the work
“a good vaccine to have ready in case of any outbreaks with this virus”
However, he thinks this approach may fall short in tackling human influenza.
“H5 changes in multiple directions, so a central antigen makes sense,
while in the human flu or human SARS-CoV-2,
the central antigen moves with time.”

One shot to rule them all in the fight against H5 influenza
New bird flu vaccine design could help preparations against an evolving potential pandemic virus 

HITTER: A HumanoId Table TEnnis Robot via Hierarchical Planning and Learning
Zhi Su, Bike Zhang, Nima Rahmanian, Yuman Gao, Qiayuan Liao, Caitlin Regan, Koushil Sreenath, S. Shankar Sastry
https://arxiv.org/abs/2508.21043

HITTER: A HumanoId Table TEnnis Robot via Hierarchical Planning and Learning
Humanoid robots have recently achieved impressive progress in locomotion and whole-body control, yet they remain constrained in tasks that demand rapid interaction with dynamic environments through manipulation. Table tennis exemplifies such a challenge: with ball speeds exceeding 5 m/s, players must perceive, predict, and act within sub-second reaction times, requiring both agility and precision. To address this, we present a hierarchical framework for humanoid table tennis that integrates a m…

Synergizing Static Analysis with Large Language Models for Vulnerability Discovery and beyond
Vaibhav Agrawal, Kiarash Ahi
https://arxiv.org/abs/2509.15433 https://

Synergizing Static Analysis with Large Language Models for Vulnerability Discovery and beyond
This report examines the synergy between Large Language Models (LLMs) and Static Application Security Testing (SAST) to improve vulnerability discovery. Traditional SAST tools, while effective for proactive security, are limited by high false-positive rates and a lack of contextual understanding. Conversely, LLMs excel at code analysis and pattern recognition but can be prone to inconsistencies and hallucinations. By integrating these two technologies, a more intelligent and efficient system is…

Leveraging Familiarity with Television to Enrich Older Adults' Engagement and Wellbeing: A Feasibility Study Using Video Probes
Shyama Sastha Krishnamoorthy Srinivasan, Mohan Kumar, Pushpendra Singh
https://arxiv.org/abs/2509.15618

Leveraging Familiarity with Television to Enrich Older Adults' Engagement and Wellbeing: A Feasibility Study Using Video Probes
The shift away from multigenerational families to nuclear families in India has created a growing need to support older adults living independently. While technology can help address this gap, older adults' limited exposure to newer technology restricts the adoption of such solutions. However, they remain comfortable with long-standing technologies like television (TV). This study explores their daily technology usage and challenges, aiming to determine whether TV can be leveraged to improve th…

Accelerating 3D Photoacoustic Computed Tomography with End-to-End Physics-Aware Neural Operators
Jiayun Wang, Yousuf Aborahama, Arya Khokhar, Yang Zhang, Chuwei Wang, Karteekeya Sastry, Julius Berner, Yilin Luo, Boris Bonev, Zongyi Li, Kamyar Azizzadenesheli, Lihong V. Wang, Anima Anandkumar
https://arxiv.org/abs/2509.09894

Accelerating 3D Photoacoustic Computed Tomography with End-to-End Physics-Aware Neural Operators
Photoacoustic computed tomography (PACT) combines optical contrast with ultrasonic resolution, achieving deep-tissue imaging beyond the optical diffusion limit. While three-dimensional PACT systems enable high-resolution volumetric imaging for applications spanning transcranial to breast imaging, current implementations require dense transducer arrays and prolonged acquisition times, limiting clinical translation. We introduce Pano (PACT imaging neural operator), an end-to-end physics-aware mod…

Crosslisted article(s) found for q-fin.RM. https://arxiv.org/list/q-fin.RM/new
[1/1]:
- Eco-Innovation and Earnings Management: Unveiling the Moderating Effects of Financial Constraints...
Probowo Erawan Sastroredjo, Marcel Ausloos, Polina Khrennikova

Supporting Socially Constrained Private Communications with SecureWhispers
Vinod Khandkar, Kieron Ivy Turk, Ehsan Toreini, Nishanth Sastry
https://arxiv.org/abs/2508.12870 https…

Supporting Socially Constrained Private Communications with SecureWhispers
Rapidly changing social norms and national, legal, and political conditions socially constrain people from discussing sensitive topics such as sexuality or religion. Such constrained, vulnerable minorities are often worried about inadvertent information disclosure and may be unsure about the extent to which their communications are being monitored in public or semi-public spaces like workplaces or cafes. Personal devices extend trust to the digital domain, making it desirable to have strictly p…

How to Combat Reactive and Dynamic Jamming Attacks with Reinforcement Learning
Yalin E. Sagduyu, Tugba Erpek, Kemal Davaslioglu, Sastry Kompella
https://arxiv.org/abs/2510.02265

How to Combat Reactive and Dynamic Jamming Attacks with Reinforcement Learning
This paper studies the problem of mitigating reactive jamming, where a jammer adopts a dynamic policy of selecting channels and sensing thresholds to detect and jam ongoing transmissions. The transmitter-receiver pair learns to avoid jamming and optimize throughput over time (without prior knowledge of channel conditions or jamming strategies) by using reinforcement learning (RL) to adapt transmit power, modulation, and channel selection. Q-learning is employed for discrete jamming-event states…

ZeroFalse: Improving Precision in Static Analysis with LLMs
Mohsen Iranmanesh (Simon Fraser University), Sina Moradi Sabet (Amirkabir University of Technology), Sina Marefat (K. N. Toosi University of Technology), Ali Javidi Ghasr (Ferdowsi University of Mashhad), Allison Wilson (Cyber Risk Solutions), Iman Sharafaldin (Forward Security), Mohammad A. Tayebi (Simon Fraser University)

ZeroFalse: Improving Precision in Static Analysis with LLMs
Static Application Security Testing (SAST) tools are integral to modern software development, yet their adoption is undermined by excessive false positives that weaken developer trust and demand costly manual triage. We present ZeroFalse, a framework that integrates static analysis with large language models (LLMs) to reduce false positives while preserving coverage. ZeroFalse treats static analyzer outputs as structured contracts, enriching them with flow-sensitive traces, contextual evidence,…

When are safety filters safe? On minimum phase conditions of control barrier functions
Jason J. Choi, Claire J. Tomlin, Shankar Sastry, Koushil Sreenath
https://arxiv.org/abs/2508.07684

When are safety filters safe? On minimum phase conditions of control barrier functions
In emerging control applications involving multiple and complex tasks, safety filters are gaining prominence as a modular approach to enforcing safety constraints. Among various methods, control barrier functions (CBFs) are widely used for designing safety filters due to their simplicity, imposing a single linear constraint on the control input at each state. In this work, we focus on the internal dynamics of systems governed by CBF-constrained control laws. Our key observation is that, althoug…