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This paper addresses the under-explored security risks in the implementation layer of local large language model (LLM) agents—software runtimes like OpenClaw and Nanobot that execute model-driven a…
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This paper investigates whether automated bystander interventions, implemented as bots replying to personal insults on Reddit, can effectively reduce the frequency of such insults
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This paper addresses the largely overlooked cryptographic security risks present in embodied AI (EAI) mobile applications, which serve as critical control-path components bridging users, cloud serv…
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This paper addresses the challenge of automating and auditing the iterative research process for developing learned control policies in aerospace guidance, navigation, and control problems
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This paper addresses the security challenge posed by model-guided automated jailbreak attacks against increasingly agentic AI systems that rely on large language models (LLMs) to interpret instruct…
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ARGUS addresses the critical challenge of always-on, fine-grained tracing and real-time performance diagnosis in production-scale GPU clusters exceeding 10,000 GPUs, specifically targeting large la…
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This paper addresses the origins of atmospheric diversity in sub-Neptune exoplanets by linking observable atmospheric compositions to the nature of their planetary building blocks—rock, water, and …
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This paper explores the application of deep reinforcement learning (RL) to augment game AI in large-scale commercial AAA titles, specifically EA SPORTS FC 25 and Battlefield 6
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This paper addresses the challenge of automatically generating explicit skill libraries (SKILL.md) for computer-using agents (CUAs) from interaction trajectory data rather than relying on hand-craf…
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This paper focuses on acoustic-to-articulatory inversion (AAI), a challenging problem of estimating continuous vocal tract movements from acoustic speech signals
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This paper addresses a fundamental inefficiency in how large language model (LLM) agents interact with web services to execute multi-step, procedural workflows
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This paper investigates the limitations of classifying scientific open-source software (OSS) projects as abandoned using fixed inactivity thresholds and instead presents a nuanced taxonomy of dorma…
