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arXiv:2602.22814v1 Announce Type: new Abstract: Agentic AI increasingly intervenes proactively by inferring users' situations from contextual data yet often fails for lack of principled judgment …
arXiv:2602.22822v1 Announce Type: new Abstract: The identification and property prediction of chemical molecules is of central importance in the advancement of drug discovery and material …
arXiv:2602.22839v1 Announce Type: new Abstract: Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing presentation agents often …
arXiv:2602.22842v1 Announce Type: new Abstract: Can artificial intelligence truly contribute to creative mathematical research, or does it merely automate routine calculations while introducing risks of …
arXiv:2602.22879v1 Announce Type: new Abstract: Knowledge Tracing (KT) diagnoses students' concept mastery through continuous learning state monitoring in education.Existing methods primarily focus on studying behavioral …
arXiv:2602.22897v1 Announce Type: new Abstract: Human intelligence naturally intertwines omni-modal perception -- spanning vision, audio, and language -- with complex reasoning and tool usage to …
arXiv:2602.22963v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have substantially advanced video misinformation detection through unified multimodal reasoning, but they often rely on …
arXiv:2602.22968v1 Announce Type: new Abstract: Understanding how neural networks arrive at their predictions is essential for debugging, auditing, and deployment. Mechanistic interpretability pursues this goal …
arXiv:2602.22971v1 Announce Type: new Abstract: As LLMs achieved breakthroughs in general reasoning, their proficiency in specialized scientific domains reveals pronounced gaps in existing benchmarks due …
arXiv:2602.22973v1 Announce Type: new Abstract: Human-in-the-loop validation is essential in safety-critical clinical AI, yet the transition between initial model inference and expert correction is rarely …
arXiv:2602.22981v1 Announce Type: new Abstract: Decoding brain activity from electroencephalography (EEG) is crucial for neuroscience and clinical applications. Among recent advances in deep learning for …
arXiv:2602.22983v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly used, their security risks have drawn increasing attention. Existing research reveals that LLMs …
