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SAM2Matting addresses the longstanding challenge of video matting, which requires both robust high-level target tracking and low-level fine-grained alpha matte estimation
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This work addresses the longstanding challenge of integrating olfaction into multimodal AI systems, which has been limited by the scarcity of paired visuo-olfactory data
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This paper addresses the computational challenges of Bayesian calibration of mechanistic epidemiological models, which are crucial for real-time public health forecasting during infectious disease …
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This paper addresses the challenge of designing efficient sparse observation networks to reduce forecast errors in ensemble-based data assimilation, particularly with the Ensemble Kalman Filter (EnKF)
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This paper addresses the critical vulnerability in 5G networks where base stations (gNBs) broadcast unauthenticated system information (SI), specifically System Information Block 1 (SIB1), enabling…
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This paper investigates the use of Waterproof, an educational proof assistant using controlled natural language, in a first-year undergraduate introductory proof course at Utrecht University
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This paper addresses the challenge of creating a unified discrete representation for both text and vision that balances semantic richness and low-level visual detail
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This paper investigates the fundamental relationship between sequence probability assigned by large language models (LLMs) and the correctness of their generated outputs
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This paper investigates when combining multiple large language models (LLMs) via routing, voting, cascades, fusion, or mixture-of-agents (MoA) can improve accuracy beyond using a single model
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This paper addresses the challenge of characterizing nonlinear distortion and noise propagation through memoryless nonlinear RF power amplifiers, particularly relevant for millimeter-wave vehicular…
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AXLE (Axiom Lean Engine) is a cloud infrastructure designed to support high-throughput, strict, and robust theorem proving utilities for the Lean 4 proof assistant
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This paper addresses a critical and underexplored problem in synthetic medical image detection — the multimodal robustness of vision-language models (VLMs) when jointly analyzing medical images and …
