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arXiv:2604.03672v1 Announce Type: new Abstract: Government agencies worldwide face growing volumes of citizen appeals, with electronic submissions increasing significantly over recent years. Traditional manual processing …
arXiv:2604.03565v1 Announce Type: new Abstract: Can lifetime learning expand behavioral diversity over evolutionary time, rather than collapsing it? Prior theory predicts that plasticity reduces variance …
arXiv:2604.03527v1 Announce Type: new Abstract: Modern agentic workflows decompose complex tasks into specialized subtasks and route them to diverse models to minimize cost without sacrificing …
arXiv:2604.03631v1 Announce Type: new Abstract: On-screen learning behavior provides valuable insights into how students seek, use, and create information during learning. Analyzing on-screen behavioral engagement …
arXiv:2604.04013v1 Announce Type: new Abstract: The increasing size and complexity of large language models (LLMs) have raised significant challenges in deployment efficiency, particularly under resource …
arXiv:2604.04017v1 Announce Type: new Abstract: Deep research agents integrate fragmented evidence through multi-step tool use. BrowseComp offers a text-only testbed for such agents, but existing …
arXiv:2604.04064v1 Announce Type: new Abstract: Small language models (SLMs) in the 100M-10B parameter range increasingly power production systems, yet whether they possess the internal emotion …
arXiv:2604.03920v1 Announce Type: new Abstract: LLM-based social simulations can generate believable community interactions, enabling ``policy wind tunnels'' where governance interventions are tested before deployment. But …
arXiv:2604.04120v1 Announce Type: new Abstract: Long chain-of-thought (Long-CoT) reasoning models have motivated a growing body of work on compressing reasoning traces to reduce inference cost, …
arXiv:2604.03335v1 Announce Type: new Abstract: Apparent age estimation is a valuable tool for business personalization, yet current models frequently exhibit demographic biases. We review prior …
arXiv:2604.03673v1 Announce Type: new Abstract: Interpretability research has highlighted the importance of evaluating Pretrained Language Models (PLMs) and in particular contextual embeddings against explicit linguistic …
arXiv:2604.04177v1 Announce Type: new Abstract: As large language models (LLMs) are increasing integrated into fact-checking pipelines, formal logic is often proposed as a rigorous means …