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This paper addresses the growing threat to automatic speaker verification (ASV) systems posed by sophisticated text-to-speech and voice cloning attacks.
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This paper addresses the challenge of generating and stabilizing steady-state long-range entanglement between two nitrogen-vacancy centers (NVCs) in diamond.
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This paper addresses the challenge of applying reinforcement learning (RL) to Masked Diffusion Language Models (MDLMs), which unlike autoregressive models.
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This paper analyzes a memory exhaustion attack on the blocklace, a Byzantine-repelling Conflict-Free Replicated Data Type (CRDT) based on authenticated.
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MIRA (Mentored Investigations using Robotic Astronomy) addresses the challenge of scaling hands-on telescope experience to larger student groups while.
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MM-IssueLoc addresses the challenge of repository-level issue localization in software engineering by explicitly incorporating visual evidence such as.
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This paper addresses the challenge of segment-level myocardial infarction (MI) localization from echocardiography (Echo) videos, which is crucial for.
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OmniaBench addresses a critical evaluation gap for general AI agents by providing a large-scale, scenario-rich benchmark covering a wide spectrum of.
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This paper addresses a fundamental limitation in on-policy distillation (OPD) for reinforcement learning-based post-training of large language models (LLMs).
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This paper investigates the effectiveness of large language model (LLM) chatbots configured with explicit political leanings to fact-check political news.
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This paper addresses the automated detection of Mild Cognitive Impairment (MCI), a subtle early cognitive decline often preceding Alzheimer's disease.
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This paper investigates whether large language models (LLMs) behave as conditional inference engines during in-context learning (ICL), specifically.
