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arXiv:2603.02658v1 Announce Type: new Abstract: Fashion intelligence spans multiple tasks, i.e., retrieval, recommendation, recognition, and dialogue, yet remains hindered by fragmented supervision and incomplete fashion...
arXiv:2603.02661v1 Announce Type: new Abstract: Blockchains are diverse in the way they handle communications between their nodes to disseminate information, mitigate attacks, and agree on...
arXiv:2603.02662v1 Announce Type: new Abstract: Well-designed indoor scenes should prioritize how people can act within a space rather than merely what objects to place. However,...
arXiv:2603.02663v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have recently emerged as general architectures capable of reasoning over diverse modalities. Benchmarks for MLLMs...
arXiv:2603.02667v1 Announce Type: new Abstract: Unifying visual representation learning and text-to-image (T2I) generation within a single model remains a central challenge in multimodal learning. We...
arXiv:2603.02668v1 Announce Type: new Abstract: We present SorryDB, a dynamically-updating benchmark of open Lean tasks drawn from 78 real world formalization projects on GitHub. Unlike...
arXiv:2603.02669v1 Announce Type: new Abstract: In modern industrial production, multiple robots often collaborate to complete complex manufacturing tasks. Large language models (LLMs), with their strong...
arXiv:2603.02675v1 Announce Type: new Abstract: Large Language Models remain vulnerable to adversarial prefix attacks (e.g., ``Sure, here is'') despite robust standard safety. We diagnose this...
arXiv:2603.02676v1 Announce Type: new Abstract: Large language models suffer from content effects in reasoning tasks, particularly in multi-lingual contexts. We introduce a novel method that...
arXiv:2603.02678v1 Announce Type: new Abstract: Learning causal structures typically represented by directed acyclic graphs (DAGs) from observational data is notoriously challenging due to the combinatorial...
arXiv:2603.02679v1 Announce Type: new Abstract: Third party advertising and tracking (A&T) are pervasive across the web, yet user exposure varies significantly with browser choice, browsing...
arXiv:2603.02680v1 Announce Type: new Abstract: While Large Language Models (LLMs) form the cornerstone of sequential decision-making agent development, they have inherent limitations in high-frequency decision...
arXiv:2603.02681v1 Announce Type: new Abstract: Visual content creation tasks demand a nuanced understanding of design conventions and creative workflows-capabilities challenging for general models, while workflow-based...
arXiv:2603.02683v1 Announce Type: new Abstract: Motion planning is a critical component of intelligent unmanned systems, enabling their complex autonomous operations. However, current planning algorithms still...
arXiv:2603.02684v1 Announce Type: new Abstract: Subtle and indirect hate speech remains an underexplored challenge in online safety research, particularly when harmful intent is embedded within...
arXiv:2603.02686v1 Announce Type: new Abstract: Despite the success of large language models (LLMs) across domains, their potential for efficient channel state information (CSI) compression and...
arXiv:2603.02687v1 Announce Type: new Abstract: This paper presents an optimized design of a Standalone Solar PV/Battery (SSPVB) system to address energy reliability and cost efficiency...
arXiv:2603.02688v1 Announce Type: new Abstract: To achieve general-purpose utility, we argue that robots must evolve from passive executors into active Information Retrieval users. In strictly...
arXiv:2603.02689v1 Announce Type: new Abstract: As the main contribution of this work we present deterministic edge coloring algorithms in the CONGEST model. In particular, we...
arXiv:2603.02690v1 Announce Type: new Abstract: Serverless wallet recovery must balance portability, usability, and privacy. Public registries enable decentralized lookup but naive identifier hashing leaks membership...
arXiv:2603.02691v1 Announce Type: new Abstract: Cold and generalized diffusion models have recently shown strong potential for sparse-view CT reconstruction by explicitly modeling deterministic degradation processes....
arXiv:2603.02692v1 Announce Type: new Abstract: Diffusion-based approaches have recently driven remarkable progress in real-world image super-resolution (SR). However, existing methods still struggle to simultaneously preserve...
arXiv:2603.02694v1 Announce Type: new Abstract: With growing discussions about the carbon footprint of academic conferences, more questions are being raised whether the environmental impacts caused...
arXiv:2603.02695v1 Announce Type: new Abstract: Multimodal data encountered in real-world scenarios are typically of low quality, with noisy modalities and missing modalities being typical forms...