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This paper addresses the dual challenge in scientific literature retrieval of deeply understanding complex, multi-constraint research intents and guaranteeing that retrieved sources are authentic a…
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This paper investigates a novel and subtle form of long-range entanglement (LRE) that arises in mixed quantum states invariant under translation symmetry
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This paper investigates how first-time international students in the United States utilize conversational AI tools, such as ChatGPT and Google Gemini, to support their cross-cultural adaptation
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WARD addresses the critical challenge of defending autonomous web agents from prompt injection attacks embedded in open web content, which can manipulate agents into executing malicious behaviors
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This paper critiques the dominant ReAct paradigm for large language model (LLM) based web agents, which interleaves reactive reasoning and acting on live, untrusted web content
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This study analyzes how cognitive operations—information campaigns aiming to influence public perception—have structurally evolved between the 2016 and 2024 U.S
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This paper addresses the challenge of reconstructing structured argument graphs from natural language text by leveraging large language models (LLMs)
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This paper surveys the emerging security threat of backdoor attacks in variational quantum circuits (VQCs), which are key components of variational quantum algorithms (VQAs) for near-term quantum c…
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Chrono::Ray is a distributed framework designed to enable high-throughput simulation-based analyses of complex multibody systems by integrating the Project Chrono physics engine with the Ray distri…
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This paper addresses Byzantine agreement protocols enhanced by classification predictions that indicate which processes are honest or faulty
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Evaluated on a purpose-built dataset of 46,454 Wazuh security events, Smart-SIEM dramatically improves detection compared to classifiers without context features, raising macro F1 from approximatel…
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This paper addresses a major limitation of current large language model (LLM) adaptation methods that optimize model context without updating weights
