research note
This paper presents and thoroughly evaluates a new class of scalable, untargeted promptware attacks called adversarial HalluSquatting against agentic LLM.
research note
This paper addresses the computational challenge of detecting short-period binary pulsars in circular orbits via fully coherent phase models.
research note
This paper addresses the challenging inverse problem of decoding physical conditions—specifically magnetic field, temperature, and magnetic history—from.
research note
This paper addresses the challenge of training autonomous web agents that can improve their tool-use abilities from their own experience without relying.
research note
This paper tackles automated detection of autism-related self-stimulatory behaviors, focusing on two main challenges: selecting optimal sequence-based.
research note
This paper addresses the challenge of optimizing long-horizon agents through reflection-based mechanisms where large language models (LLMs) optimize agent.
research note
This paper investigates the potential for small, generalist Vision-Language Models (VLMs) to perform zero-shot classification of Fast Radio Bursts (FRBs).
research note
This paper investigates the complementary roles of human chemists and Large Language Models (LLMs) in predicting solid-state synthesis routes for known.
research note
This paper addresses the longstanding challenge of accurately estimating the state of charge (SOC) in lithium-ion batteries, which is difficult due to.
research note
This paper addresses the practical reliability challenges of time-constrained authentication workflows in USSD-based financial services, which are.
research note
This paper addresses the critical challenge of enabling secure and privacy-preserving electronic voting without relying on a trusted key dealer.
research note
This paper addresses the complex ordering and defect dynamics in nematopolar systems—materials exhibiting coexisting polar and nematic symmetries that.
