Tootfinder

OPM: Trump’s hiring questions ‘mandatory’ for agencies to ask, but optional for candidates to answer
https://federalnewsnetwork.com/workforce/2025/08/opm-trumps-hiring-questions-mandatory-for-agencies-to-ask-but-optional-for-candidates-to-answer/

After release from captivity, Russian POWs often 'sent back to die' in Ukraine: https://benborges.xyz/2025/09/15/after-release-from-captivity-russian.html

Multi-task Adversarial Attacks against Black-box Model with Few-shot Queries
Wenqiang Wang, Yan Xiao, Hao Lin, Yangshijie Zhang, Xiaochun Cao
https://arxiv.org/abs/2508.10039 ht…

Multi-task Adversarial Attacks against Black-box Model with Few-shot Queries
Current multi-task adversarial text attacks rely on abundant access to shared internal features and numerous queries, often limited to a single task type. As a result, these attacks are less effective against practical scenarios involving black-box feedback APIs, limited queries, or multiple task types. To bridge this gap, we propose \textbf{C}luster and \textbf{E}nsemble \textbf{M}ulti-task Text Adversarial \textbf{A}ttack (\textbf{CEMA}), an effective black-box attack that exploits the transf…

A new attack was shown to use AI to hack into Gmail accounts.
“It illustrates why developing robust protections against prompt injection attacks is important."
Direct and indirect prompt injection attacks hide instructions for AI assistants in emails, messages, websites, attachments and calendar invites.
You won’t see them, but your AI assistant will. -- And all too often that assistant will do as it’s told.
This threat “is not specific to Google," the compan…

Google Confirms Gmail Warning — New Attack Hacks Your Email
"AI might be super smart but it can be tricked" — change your account settings now as new threat revealed.

Normalized Ambiguity Function Characteristics of OFDM, OTFS, AFDM, and CP-AFDM for ISAC
Hyeon Seok Rou, Giuseppe Thadeu Freitas de Abreu
https://arxiv.org/abs/2510.11216 https:/…

Normalized Ambiguity Function Characteristics of OFDM, OTFS, AFDM, and CP-AFDM for ISAC
This paper presents a unified and system-agnostic analysis of the ambiguity function (AF) characteristics of four representative multicarrier waveforms, orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS), affine frequency division multiplexing (AFDM), and chirp-permuted AFDM (CP-AFDM), which are considered as key candidates for enabling integrated sensing and communications (ISAC) in future sixth generation (6G) networks. The AF of each waveform is obtaine…

Joe Burrow injury: Bengals' QB options beyond Jake Browning https://www.nytimes.com/athletic/6631474/2025/09/15/bengals-joe-burrow-injury-cousins-winston/

A Physics-Informed Reinforcement Learning Approach for Degradation-Aware Long-Term Charging Optimization in Batteries
Shanthan Kumar Padisala, Bharatkumar Hegde, Ibrahim Haskara, Satadru Dey
https://arxiv.org/abs/2510.11515

A Physics-Informed Reinforcement Learning Approach for Degradation-Aware Long-Term Charging Optimization in Batteries
Batteries degrade with usage and continuous cycling. This aging is typically reflected through the resistance growth and the capacity fade of battery cells. Over the years, various charging methods have been presented in the literature that proposed current profiles in order to enable optimal, fast, and/or health-conscious charging. However, very few works have attempted to make the ubiquitous Constant Current Constant Voltage (CCCV) charging protocol adaptive to the changing battery health as …

Why Report Failed Interactions With Robots?! Towards Vignette-based Interaction Quality
Agnes Axelsson, Merle Reimann, Ronald Cumbal, Hannah Pelikan, Divesh Lala
https://arxiv.org/abs/2508.10603

Why Report Failed Interactions With Robots?! Towards Vignette-based Interaction Quality
Although the quality of human-robot interactions has improved with the advent of LLMs, there are still various factors that cause systems to be sub-optimal when compared to human-human interactions. The nature and criticality of failures are often dependent on the context of the interaction and so cannot be generalized across the wide range of scenarios and experiments which have been implemented in HRI research. In this work we propose the use of a technique overlooked in the field of HRI, eth…

Model-agnostic post-hoc explainability for recommender systems
Irina Ar\'evalo, Jose L Salmeron
https://arxiv.org/abs/2509.10245 https://arxiv.org/pdf/…

Model-agnostic post-hoc explainability for recommender systems
Recommender systems often benefit from complex feature embeddings and deep learning algorithms, which deliver sophisticated recommendations that enhance user experience, engagement, and revenue. However, these methods frequently reduce the interpretability and transparency of the system. In this research, we develop a systematic application, adaptation, and evaluation of deletion diagnostics in the recommender setting. The method compares the performance of a model to that of a similar model tr…

Pharmacist: Safety Alignment Data Curation for Large Language Models against Harmful Fine-tuning
Guozhi Liu, Qi Mu, Tiansheng Huang, Xinhua Wang, Li Shen, Weiwei Lin, Zhang Li
https://arxiv.org/abs/2510.10085

Pharmacist: Safety Alignment Data Curation for Large Language Models against Harmful Fine-tuning
Harmful fine-tuning issues present significant safety challenges for fine-tuning-as-a-service in large language models. Existing alignment-stage defenses, e.g., Vaccine, Repnoise, Booster, and T-Vaccine, mitigate harmful fine-tuning issues by enhancing the model's robustness during the alignment phase. While these methods have been proposed to mitigate the issue, they often overlook a critical upstream factor: the role of the original safety-alignment data. We observe that their defense perform…