Final-answer accuracy reports whether a vision-language model was right, but not whether its answer was grounded in the image, whether its stated reasoning reflects that evidence, or what the answer cost to produce. Those are the properties that decide whether a system can be deployed. We present PRISM-BENCH, a benchma...
Vansh Bhatia, Mehdi Rezagholizadeh, Parsa Ashrafi Fashi et al.· 0 citations
Zebra3D, a layerwise sparse-linear hybrid attention framework that improves the efficiency of pretrained 3D foundation models without training from scratch, achieves strong reconstruction and camera-pose accuracy at high attention sparsity, with training-free variants remaining close to their dense counterparts.
Utkarsh Saxena, Rui-Jing Yang, Mehdi Rezagholizadeh et al.· 0 citations
Instella-MoE is introduced, a fully open Mixture-of-Experts (MoE) language model with 16 billion total parameters and 2.8 billion active parameters per token trained entirely from scratch on AMD Instinct MI300X and MI325X GPUs, establishing a strong, fully open foundation for efficient, high-performing MoE models and r...
Jiang Liu, Sudhanshu Ranjan, Prakamya Mishra et al.· 0 citations
A rendering-aware Bayesian 3DGS framework that tracks Gaussian geometry with a Normal-Inverse-Wishart posterior over means and covariances using renderer-derived surrogate summaries is introduced, positioning Bayesian 3DGS as a practical probabilistic scene representation for decision-facing tasks such as active view s...
Gao-Xiang Jia, Vikram V. Appia, Jun-Zhou Huang et al.· arXiv.org· 2 citations
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