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arXiv:2602.11618v2 Announce Type: replace Abstract: Chemical Language Models (CLMs) pre-trained on large scale molecular data are widely used for molecular property prediction. However, the common...
arXiv:2602.11897v2 Announce Type: replace Abstract: Contemporary AI-driven cybersecurity systems are predominantly architected as model-centric detection and automation pipelines optimized for task-level performance metrics such as...
arXiv:2602.11938v4 Announce Type: replace Abstract: Large language models (LLMs) perform well on well-posed questions, yet standard question-answering (QA) benchmarks remain far from solved. We argue...
arXiv:2602.12249v2 Announce Type: replace Abstract: Despite speech recognition systems achieving low word error rates on standard benchmarks, they often fail on short, high-stakes utterances in...
arXiv:2602.12430v3 Announce Type: replace Abstract: The transition from monolithic language models to modular, skill-equipped agents marks a defining shift in how large language models (LLMs)...
arXiv:2602.12444v2 Announce Type: replace Abstract: Reinforcement learning (RL) is a powerful framework for optimal decision-making and control but often lacks provable guarantees for safety-critical applications....
arXiv:2602.12694v2 Announce Type: replace Abstract: Ultra-low-density elastomeric foams enable lightweight systems that combine high compliance with efficient energy return. In high-performance racing shoes, these foams...
arXiv:2602.12794v2 Announce Type: replace Abstract: The emerging integration of robots into everyday life brings several major challenges. Compared to classical industrial applications, more flexibility is...
arXiv:2602.12800v2 Announce Type: replace Abstract: We study the amount of reliable information that can be stored in a DNA-based storage system with noisy sequencing, where...
arXiv:2602.12937v2 Announce Type: replace Abstract: Being modeled as a single-label classification task for a long time, recent work has argued that Arabic Dialect Identification (ADI)...
arXiv:2602.13154v3 Announce Type: replace Abstract: Foundational results in machine learning -- the universal approximation theorem and deep reinforcement learning convergence -- imply that the vast...
arXiv:2602.13351v2 Announce Type: replace Abstract: Finite automata (FA) are a fundamental computational abstraction that is widely used in practice for various tasks in computer science,...
arXiv:2602.13629v2 Announce Type: replace Abstract: As Artificial Intelligence (AI) becomes increasingly integrated into education, university students preparing for English language tests are frequently shifting between...
arXiv:2602.13662v2 Announce Type: replace Abstract: Foundation models and vision-language pre-training have significantly advanced Vision-Language Models (VLMs), enabling multimodal processing of visual and linguistic data. However,...
arXiv:2602.13812v2 Announce Type: replace Abstract: Document-to-table (Doc2Table) extraction derives structured tables from unstructured documents under a target schema, enabling reliable and verifiable SQL-based data analytics....
arXiv:2602.13920v2 Announce Type: replace Abstract: Recent advances in agent-mediated systems have enabled a new paradigm of social network simulation, where AI agents interact with human-like...
arXiv:2602.14027v2 Announce Type: replace Abstract: Autoregressive video diffusion models have emerged as a scalable paradigm for long video generation. However, they often suffer from severe...
arXiv:2602.14073v2 Announce Type: replace Abstract: Most vision-language models (VLMs) are trained on English-centric data, limiting their performance in other languages and cultural contexts. This restricts...
arXiv:2602.14392v2 Announce Type: replace Abstract: Positivity preservation of key physical quantities in the context of fluid flows, such as density and internal energy, is an...
arXiv:2602.14492v2 Announce Type: replace Abstract: Industrial-scale user representation learning requires balancing robust universality with acute task-sensitivity. However, existing paradigms primarily yield static, task-agnostic embeddings that...
arXiv:2602.14572v2 Announce Type: replace Abstract: CI/CD practices play a significant role during collaborative software development by automating time-consuming and repetitive tasks such as testing, building,...
arXiv:2602.14622v2 Announce Type: replace Abstract: Association Rule Mining (ARM) is a fundamental task for knowledge discovery in tabular data and is widely used in high-stakes...
arXiv:2602.14643v2 Announce Type: replace Abstract: Large language models struggle to maintain strict adherence to structured workflows in high-stakes domains such as healthcare triage. Monolithic approaches...
arXiv:2602.14674v2 Announce Type: replace Abstract: Gradual argumentation is a field of symbolic AI which is attracting attention for its ability to support transparent and contestable...