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arXiv:2603.13353v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly positioned as scalable tools for annotating educational data, including classroom discourse, interaction logs, and …
arXiv:2603.13818v1 Announce Type: new Abstract: Precipitation nowcasting is vital for flood warning, agricultural management, and emergency response, yet two bottlenecks persist: the prohibitive cost of …
arXiv:2603.13545v1 Announce Type: new Abstract: AI development has a fiction dependency problem: models are built on massive corpora of modern fiction and desperately need more …
arXiv:2603.13683v1 Announce Type: new Abstract: Although debiased LLMs perform well on known bias patterns, they often fail to generalize to unfamiliar bias prompts, producing toxic …
arXiv:2603.14041v1 Announce Type: new Abstract: The enhancement of reasoning capabilities in large language models (LLMs) has garnered significant attention, with supervised fine-tuning (SFT) and reinforcement …
arXiv:2603.13696v1 Announce Type: new Abstract: We present the first systematic evaluation of mutual exclusivity (ME) -- the bias to map novel words to novel referents …
arXiv:2603.13236v1 Announce Type: new Abstract: AI-related incidents are becoming increasingly frequent and severe, ranging from safety failures to misuse by malicious actors. In such complex …
arXiv:2603.13239v1 Announce Type: new Abstract: Smart contracts play a central role in blockchain systems by encoding financial and operational logic. Still, their susceptibility to subtle …
arXiv:2603.13243v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) generate text via iterative denoising but consistently underperform on multi-step reasoning. We hypothesize this gap …
arXiv:2603.13348v1 Announce Type: new Abstract: Tool use represents a critical capability for AI agents, with recent advances focusing on leveraging reinforcement learning (RL) to scale …
arXiv:2603.13834v1 Announce Type: new Abstract: Predicting the mechanical properties of polysulfone (PSF) membranes from structural descriptors remains challenging due to extreme data scarcity typical of …
arXiv:2603.13246v1 Announce Type: new Abstract: This paper proposes a Hadith-inspired multi-axis trust modeling framework, motivated by a structurally analogous problem in classical Hadith scholarship: assessing …