Academic
arXiv:2602.20580v1 Announce Type: new Abstract: Modern language models (LM) are trained on large scrapes of the Web, containing millions of personal information (PI) instances, many …
arXiv:2602.21268v1 Announce Type: new Abstract: Soft set theory provides a direct framework for parameterized decision modeling by assigning to each attribute (parameter) a subset of …
arXiv:2602.21351v1 Announce Type: new Abstract: The rapid accumulation of Earth science data has created a significant scalability challenge; while repositories like PANGAEA host vast collections …
arXiv:2602.21496v1 Announce Type: new Abstract: While defenses for structured PII are mature, Large Language Models (LLMs) pose a new threat: Semantic Sensitive Information (SemSI), where …
arXiv:2602.21534v1 Announce Type: new Abstract: Agentic reinforcement learning (ARL) has rapidly gained attention as a promising paradigm for training agents to solve complex, multi-step interactive …
arXiv:2602.21556v1 Announce Type: new Abstract: When designing compound AI systems, a common approach is to query multiple copies of the same model and aggregate the …
arXiv:2602.21745v1 Announce Type: new Abstract: We introduce the ASIR (Awakened Shared Intelligence Relationship) Courage Model, a phase-dynamic framework that formalizes truth-disclosure as a state transition …
arXiv:2602.21746v1 Announce Type: new Abstract: In a previous work, we introduced the fuzzy Ethical Decision-Making framework (fEDM), a risk-based ethical reasoning architecture grounded in fuzzy …
arXiv:2602.21814v1 Announce Type: new Abstract: Large language models consistently fail the "car wash problem," a viral reasoning benchmark requiring implicit physical constraint inference. We present …
arXiv:2602.21857v1 Announce Type: new Abstract: Complex claim verification requires decomposing sentences into verifiable subclaims, yet existing methods struggle to align decomposition quality with verification performance. …
arXiv:2602.21858v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made significant progress in mobile agent development, yet their capabilities are predominantly confined to …
arXiv:2602.21889v1 Announce Type: new Abstract: Across a growing number of fields, human decision making is supported by predictions from AI models. However, we still lack …
