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arXiv:2603.19253v1 Announce Type: cross Abstract: Argument mining (AM) is an interdisciplinary research field focused on the automatic identification and classification of argumentative components, such as …
arXiv:2603.19248v1 Announce Type: cross Abstract: Immersive conversational systems in production face a persistent trade-off between responsiveness and long-horizon task capability. Real-time interaction is achievable for …
arXiv:2603.19247v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into high-stakes applications, making robust safety guarantees a central practical and commercial concern. …
arXiv:2603.19514v1 Announce Type: new Abstract: Mathematical reasoning demands two critical, complementary skills: constructing rigorous proofs for true statements and discovering counterexamples that disprove false ones. …
arXiv:2603.19263v1 Announce Type: cross Abstract: This study examined how high school students with different motivational profiles use generative AI tools in math and writing. Through …
arXiv:2603.19896v1 Announce Type: new Abstract: Tool-using large language model (LLM) agents often face a fundamental tension between answer quality and execution cost. Fixed workflows are …
arXiv:2603.19258v1 Announce Type: cross Abstract: While differentially private (DP) fine-tuning of large language models (LLMs) is a powerful tool, it is often computationally prohibitive or …
arXiv:2603.17765v1 Announce Type: cross Abstract: Automated radiology report generation has gained increasing attention with the rise of deep learning and large language models. However, fully …
arXiv:2603.19429v1 Announce Type: new Abstract: Classical planning problems are typically defined using lifted first-order representations, which offer compactness and generality. While most planners ground these …
arXiv:2603.19954v1 Announce Type: new Abstract: Transformers have shown inconsistent success in AI planning tasks, and theoretical understanding of when generalization should be expected has been …
arXiv:2603.19685v1 Announce Type: new Abstract: Large language model (LLM)-based agents have emerged as powerful autonomous controllers for digital environments, including mobile interfaces, operating systems, and …
arXiv:2603.19255v1 Announce Type: cross Abstract: Despite the strong performance of Large Language Models (LLMs) on complex instruction-following tasks, precise control of output length remains a …