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arXiv:2603.11756v1 Announce Type: new Abstract: Deep generative models for anomaly detection in multivariate time-series are typically trained by maximizing data likelihood. However, likelihood in observation …
arXiv:2603.11721v1 Announce Type: new Abstract: Large language model (LLM) agents extend conventional generative models by integrating reasoning, tool invocation, and persistent memory. Recent studies suggest …
arXiv:2603.11631v1 Announce Type: new Abstract: Large vision-language models (LVLMs) struggle to reliably detect visual primitives in charts and align them with semantic representations, which severely …
arXiv:2603.11594v1 Announce Type: new Abstract: Chemotherapy for cancer treatment is costly and accompanied by severe side effects, highlighting the critical need for early prediction of …
arXiv:2603.11816v1 Announce Type: new Abstract: Traffic forecasting is a cornerstone of intelligent transportation systems. While existing research has made significant progress in short-term prediction, long-term …
arXiv:2603.11076v1 Announce Type: new Abstract: Recent work synthesizes agentic tasks for post-training tool-using LLMs, yet robust generalization under shifts in tasks and toolsets remains an …
arXiv:2603.11093v1 Announce Type: new Abstract: The development of high-level autonomous driving (AD) is shifting from perception-centric limitations to a more fundamental bottleneck, namely, a deficit …
arXiv:2603.11770v1 Announce Type: new Abstract: This work describes an automatic text classification method implemented in a software tool called NETHIC, which takes advantage of the …
arXiv:2603.11412v1 Announce Type: new Abstract: Under surprisal theory, linguistic representations affect processing difficulty only through the bottleneck of surprisal. Our best estimates of surprisal come …
arXiv:2603.11736v1 Announce Type: new Abstract: In recent years, generative artificial intelligence (GenAI) systems have assumed increasingly crucial roles in selection processes, personnel recruitment and analysis …
arXiv:2603.11223v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) over Knowledge Graphs (KGs) suffers from the fact that indexing approaches may lose important contextual nuance when …
arXiv:2603.11382v1 Announce Type: new Abstract: Autonomous agents, especially delegated systems with memory, persistent context, and multi-step planning, pose a measurement problem not present in stateless …