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arXiv:2509.22500v2 Announce Type: replace Abstract: Constrained optimization is a powerful framework for enforcing requirements on neural networks. These constrained deep learning problems are typically solved...
arXiv:2509.23516v4 Announce Type: replace Abstract: Delay-coupled systems often require low-latency decisions from sparse telemetry, where dense fixed-step neural inference is wasteful and can degrade near...
arXiv:2509.23525v2 Announce Type: replace Abstract: AI creates and exacerbates privacy risks, yet practitioners lack effective resources to identify and mitigate these risks. We present Privy,...
arXiv:2509.24386v2 Announce Type: replace Abstract: We have recently observed the commercial roll-out of robotaxis in various countries. They are deployed within an operational design domain...
arXiv:2509.24765v5 Announce Type: replace Abstract: Logical reasoning is a fundamental capability of large language models. However, existing studies often overlook the interaction between logical complexity...
arXiv:2509.25041v3 Announce Type: replace Abstract: Sparse Mixture of Experts (SMoE) performs conditional computation by selectively activating a subset of experts, thereby enabling scalable parameter growth...
arXiv:2509.25178v2 Announce Type: replace Abstract: Object hallucination in Multimodal Large Language Models (MLLMs) is a persistent failure mode that causes the model to perceive objects...
arXiv:2509.25204v2 Announce Type: replace Abstract: Entropy-based inference methods have gained traction for improving the reliability of Large Language Models (LLMs). However, many existing approaches, such...
arXiv:2509.25236v2 Announce Type: replace Abstract: Causal artificial intelligence aims to improve explainability, robustness, and trustworthiness by leveraging causal models. Recent work has shown that sheaf-theoretic...
arXiv:2509.26136v2 Announce Type: replace Abstract: With their growing capabilities, generative large language models (LLMs) are being increasingly investigated for complex medical tasks. However, their effectiveness...
arXiv:2510.00472v2 Announce Type: replace Abstract: We introduce capital games, which generalize the definition of standard games to incorporate dynamics. In capital games, payoffs are in...
arXiv:2510.01399v2 Announce Type: replace Abstract: State-of-the-art text-to-image models demonstrate impressive realism but suffer from a persistent identity crisis when generating scenes with multiple humans: producing...
arXiv:2510.01812v4 Announce Type: replace Abstract: Singing voice generation progresses rapidly, yet evaluating singing quality remains a critical challenge. Human subjective assessment, typically in the form...
arXiv:2510.02712v3 Announce Type: replace Abstract: Large Language Models (LLMs) have revolutionized conversational AI, yet their robustness in extended multi-turn dialogues remains poorly understood. Existing evaluation...
arXiv:2510.03437v2 Announce Type: replace Abstract: Kernel change-point detection (KCPD) has become a widely used tool for identifying structural changes in complex data. While existing theory...
arXiv:2510.03906v2 Announce Type: replace Abstract: Autonomous driving perception systems are particularly vulnerable in foggy conditions, where light scattering reduces contrast and obscures fine details critical...
arXiv:2510.04182v4 Announce Type: replace Abstract: Recent advancements in Large Language Models (LLMs) have shifted from explicit Chain-of-Thought (CoT) reasoning to more efficient latent reasoning, where...
arXiv:2510.04905v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have substantially improved automated code generation. While function-level and file-level generation have achieved...
arXiv:2510.05749v2 Announce Type: replace Abstract: Continuous dimensional speech emotion recognition captures affective variation along valence, arousal, and dominance, providing finer-grained representations than categorical approaches. Yet...
arXiv:2510.05758v2 Announce Type: replace Abstract: Recent LLM-based TTS systems achieve strong quality and zero-shot ability, but lack fine-grained emotional control due to their reliance on...
arXiv:2510.05840v2 Announce Type: replace Abstract: Accurate travel time estimation (TTE) plays a crucial role in intelligent transportation systems. However, it remains challenging due to heterogeneous...
arXiv:2510.06700v2 Announce Type: replace Abstract: Both humans and large language models (LLMs) exhibit content effects: biases in which the plausibility of the semantic content of...
arXiv:2510.06913v2 Announce Type: replace Abstract: Realistic traffic simulation is critical for the development of autonomous driving systems and urban mobility planning, yet existing imitation learning...
arXiv:2510.07713v2 Announce Type: replace Abstract: The primary form of user-internet engagement is shifting from leveraging implicit feedback signals, such as browsing and clicks, to harnessing...