CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning
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: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…
arXiv:2607.11436v1 Announce Type: new Abstract: Vision-language models increasingly succeed on multimodal reasoning benchmarks, yet their visual evidence often becomes unstable…
arXiv:2508.14817v2 Announce Type: replace-cross Abstract: Objective: To evaluate whether retrieval-augmented generation (RAG) can serve as an efficient alternative to long-context…
arXiv:2601.10034v2 Announce Type: cross Abstract: Decision making often exhibits context dependence that challenges classical probability theory. This paper develops a…
arXiv:2511.00651v2 Announce Type: replace Abstract: Telecom networks are rapidly growing in scale and complexity, making effective management, operation, and optimization…