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This paper addresses the problem of robust self-supervised monocular depth estimation for autonomous driving under diverse and adverse weather conditions.
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This paper presents a detailed case study integrating a Large Language Model (LLM) with the Logic Program Theorem Prover (LPTP) to formally prove the.
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This paper addresses a critical but underappreciated challenge in migrating public-key infrastructure (PKI) to post-quantum cryptography through hybrid.
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This paper addresses identifying distinct dynamical complexity regimes and sharp transitions in the far-from-equilibrium quantum dynamics of the Dicke.
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This paper addresses explainability challenges in deep learning models for retinal disease classification from fundus images, a clinically important task.
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This paper presents CRAFT, a novel approach to support fiction writers using wearable AI smart glasses that facilitate transforming real-world.
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This paper addresses the mismatch between existing Indonesian cultural commonsense benchmarks, which rely on short, isolated prompts, and the inherently.
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DAGForge addresses the bottleneck in biomedical causal inference research caused by the manual and non-auditable process of constructing directed acyclic.
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This paper addresses the fine-grained challenge of detecting exactly which tokens in a mixed human-LLM coauthored text are generated by an LLM, rather.
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This paper addresses fundamental limitations in large language model (LLM)-empowered recommender systems that predominantly rely on autoregressive.
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This paper addresses the pervasive problem of cheating by large language model (LLM) agents on cybersecurity benchmarks, specifically capture-the-flag.
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This work addresses a key challenge in cavity quantum electrodynamics (cavity-QED) technologies: achieving high-cooperativity optical interfaces.
