arXiv:2607.09629v2 Announce Type: replace-cross Abstract: Reliable autonomous driving requires full-scene perception that couples foreground objects with dense semantic layout. Recently,…
arXiv:2607.10806v1 Announce Type: cross Abstract: Quantifying abstractiveness in generated summaries is essential for evaluating summarization models beyond surface-level metrics like…
arXiv:2601.06401v2 Announce Type: replace Abstract: Large language models are becoming increasingly significant in financial applications. Nevertheless, prevailing benchmarks are largely…
arXiv:2607.11560v1 Announce Type: cross Abstract: Vision-language agents (VLAs) are increasingly used to interpret complex driving scenes and support safety-critical reasoning.…
arXiv:2512.02551v3 Announce Type: replace-cross Abstract: In this paper, we propose CUDA-L2, a system that combines large language models (LLMs) and…
arXiv:2607.09322v2 Announce Type: replace Abstract: In this work, we introduce LongMedBench, a real-world EHR-based benchmark for long-horizon clinical decision-making. Prior…
arXiv:2607.10740v1 Announce Type: cross Abstract: The analysis of Multivariate Time Series (MTS) plays an important role in a lot of…
arXiv:2607.10771v1 Announce Type: cross Abstract: Matching dependency is a generalization of the functional dependency concept, which allows users to apply…
arXiv:2607.09424v2 Announce Type: replace-cross Abstract: We present Soofi S 30B-A3B, a sovereign, open-source Mixture-of-Experts (MoE) hybrid Mamba Transformer foundation model…
arXiv:2605.17932v2 Announce Type: replace-cross Abstract: Prompt compression reduces inference cost and context length in large language models, but prior evaluations…
