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arXiv:2601.20370v1 Announce Type: new Abstract: We introduce APPL (Abstract Program Property Logic), a unifying Hoare-style logic that subsumes standard Hoare logic, incorrectness logic, and several...
arXiv:2601.20374v1 Announce Type: new Abstract: The current digital era, driven by growing threats to data security, requires a robust image encryption technique. Classical encryption algorithms...
arXiv:2601.20375v1 Announce Type: new Abstract: Large Language Models (LLMs) can be fine-tuned on domain-specific data to enhance their performance in specialized fields. However, such data...
arXiv:2601.20377v1 Announce Type: new Abstract: Accurate material identification plays a crucial role in embodied AI systems, enabling a wide range of applications. However, current vision-based...
arXiv:2601.20378v1 Announce Type: new Abstract: As Open Radio Access Network (O-RAN) deployments expand and adversaries adopt 'store-now, decrypt-later' strategies, operators need empirical data on the...
arXiv:2601.20379v1 Announce Type: new Abstract: Large language models (LLMs) struggle with complex, long-horizon reasoning due to instability caused by their frozen policy assumption. Current test-time...
arXiv:2601.20380v1 Announce Type: new Abstract: Graphical User Interface (GUI) agents show great potential for enabling foundation models to complete real-world tasks, revolutionizing human-computer interaction and...
arXiv:2601.20381v1 Announce Type: new Abstract: Visual foundation models provide strong perceptual features for robotics, but their dense representations lack explicit object-level structure, limiting robustness and...
arXiv:2601.20382v1 Announce Type: new Abstract: The software engineering researchers from countries with smaller economies, particularly non-English speaking ones, represent valuable minorities within the software engineering...
arXiv:2601.20383v1 Announce Type: new Abstract: Text-driven multi-human motion generation with complex interactions remains a challenging problem. Despite progress in performance, existing offline methods that generate...
arXiv:2601.20385v1 Announce Type: new Abstract: The Talking Face Generation task has enormous potential for various applications in digital humans and agents, etc. Singing, as a...
arXiv:2601.20389v1 Announce Type: new Abstract: This study addresses the challenge of accurately identifying multi-task contention types in high-dimensional system environments and proposes a unified contention...
arXiv:2601.20391v1 Announce Type: new Abstract: Diffusion-Augmented Interactive Text-to-Image Retrieval (DAI-TIR) is a promising paradigm that improves retrieval performance by generating query images via diffusion models...
arXiv:2601.20394v1 Announce Type: new Abstract: Language workbenches are tools that enable the definition, reuse, and composition of programming languages and their ecosystems, aiming to streamline...
arXiv:2601.20397v1 Announce Type: new Abstract: Heterogeneous federated learning (HFL) aims to ensure effective and privacy-preserving collaboration among different entities. As newly joined clients require significant...
arXiv:2601.20400v1 Announce Type: new Abstract: Private Set Multi-Party Computations are protocols that allow parties to jointly and securely compute functions: apart from what is deducible...
arXiv:2601.20401v1 Announce Type: new Abstract: Time series forecasting presents significant challenges due to the complex temporal dependencies at multiple time scales. This paper introduces ScatterFusion,...
arXiv:2601.20402v1 Announce Type: new Abstract: Large Language Models (LLMs) have emerged as powerful learning tools, but they lack awareness of learners' cognitive and physiological states,...
arXiv:2601.20404v1 Announce Type: new Abstract: AI coding agents such as Codex and Claude Code are increasingly used to autonomously contribute to software repositories. However, little...
arXiv:2601.20407v1 Announce Type: new Abstract: Greedy methods have recently been successfully applied to generalized kernel interpolation, or the recovery of a function from data stemming...
arXiv:2601.20408v1 Announce Type: new Abstract: Enterprise LLM deployment faces a critical scalability challenge: organizations must optimize models systematically to scale AI initiatives within constrained compute...
arXiv:2601.20409v1 Announce Type: new Abstract: Time series forecasting requires capturing patterns across multiple temporal scales while maintaining computational efficiency. This paper introduces AWGformer, a novel...
arXiv:2601.20411v1 Announce Type: new Abstract: In this work, we explore an energy-efficient implementation of the polyphase network for a filter bank multicarrier (FBMC) system. The...
arXiv:2601.20412v1 Announce Type: new Abstract: The ability of Large Language Models (LLMs) to use external tools unlocks powerful real-world interactions, making rigorous evaluation essential. However,...