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arXiv:2605.19035v1 Announce Type: new Abstract: The rapid advancement of Large Language Models has given rise to autonomous LLM-based agents capable of complex reasoning and execution. As these agents…
arXiv:2605.19031v1 Announce Type: new Abstract: Kolmogorov-Arnold Networks (KANs) have demonstrated an exceptional ability to learn complex functions on clean, low-dimensional data but struggle to mai…
arXiv:2605.19010v1 Announce Type: new Abstract: Natural language to SQL (NL2SQL) conversion is an important problem for researchers and enterprises due to the ubiquitous importance of relational datab…
arXiv:2605.19008v1 Announce Type: new Abstract: Modern language-model training is increasingly exposed to instability, degraded runs, and wasted compute, especially under aggressive learning-rate, sca…
arXiv:2605.18937v1 Announce Type: new Abstract: Patient-managed Personal Health Records (PHRs) promises to empower patients to better understand their health; but information in the record is complex,…
arXiv:2605.18818v1 Announce Type: new Abstract: Academic research tends to focus on new models for document understanding creating a wide gap in the literature between model definition and running mod…
arXiv:2605.18801v1 Announce Type: new Abstract: Data is fundamental to large language models (LLMs). However, understanding of what makes certain data useful for different stages of an LLM workflow, i…
arXiv:2605.19698v1 Announce Type: new Abstract: Text-to-image diffusion models are increasingly developed through open-source reuse and repeated downstream fine-tuning, where reused checkpoints are di…
arXiv:2605.19668v1 Announce Type: new Abstract: Critical-infrastructure operators are increasingly expected to assess and remediate vulnerabilities in deployed industrial software. However, much of th…
arXiv:2605.19644v1 Announce Type: new Abstract: Knowledge Graphs (KGs) are a powerful representation of linked data, offering flexibility, semantic richness, and support for knowledge enrichment and r…
arXiv:2605.19478v1 Announce Type: new Abstract: Existing ViT backdoor attacks based on backbone-overwriting full-tuning are computationally expensive and inflict performance degradation. This has forc…
arXiv:2605.19448v1 Announce Type: new Abstract: An Intrusion Detection System (IDS) is vital in cybersecurity, detecting unauthorized activity across networks. With attacks on network layers increasin…
arXiv:2605.19402v1 Announce Type: new Abstract: Pseudorandom codes (PRCs), introduced by Christ and Gunn (CRYPTO '2024), are error-correcting codes whose codewords are computationally indistinguishabl…
arXiv:2605.19367v1 Announce Type: new Abstract: University cybersecurity protocols have intensified dramatically in response to rising threats of data breaches, ransomware, and credential theft. While…
arXiv:2605.19328v1 Announce Type: new Abstract: Recent advances in Vision-Language Models (VLMs) facilitate a new class of embodied AI systems, where these models are integrated into physical platform…
arXiv:2605.19321v1 Announce Type: new Abstract: Large Language Model (LLM) alignment remains vulnerable to jailbreak attacks that elicit unsafe responses, motivating pre-model and post-model guards. P…
arXiv:2605.19312v1 Announce Type: new Abstract: As part of the political process, citizens may participate in signature collections to influence policy changes. In Switzerland, this even results in le…
arXiv:2605.19253v1 Announce Type: new Abstract: Over-the-air federated learning (OTA-FL) improves communication efficiency by exploiting the superposition property of wireless channels, but this same …
arXiv:2605.19233v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) are cyber-physical systems whose attack surface spans networked avionics and on-board sensor fusion: a compromised GPS o…
arXiv:2605.19232v1 Announce Type: new Abstract: Fake Base Station (FBS) detection has been a critical focus of cellular security research for over two decades. However, significant financial and regul…
arXiv:2605.19227v1 Announce Type: new Abstract: Unified autoregressive models (UAMs) are transformer models that generate text as well as image tokens within a single autoregressive pass. Shared param…
arXiv:2605.19159v1 Announce Type: new Abstract: Prompt injection attacks pose significant risks to language model safety, yet existing defenses are typically evaluated using classification performance…
arXiv:2605.19147v1 Announce Type: new Abstract: Large language models (LLMs) are highly susceptible to backdoor attacks (BAs), wherein training samples are poisoned using trigger-based harmful content…
arXiv:2605.19123v1 Announce Type: new Abstract: Cryptographic primitives such as stream ciphers,Pseudorandom Number Generators (PRNGs), and block cipher modes produce sequences that are designed to be…