Model Detail
Reasoning-Medical0.1-27B
—Reasoning-Medical0.1-27B is a multimodal model with 27B parameters released by EpistemeAI. The model is registered under the image-text-to-text pipeline tag on Hugging Face, released under the cc license.
Reasoning-Medical0.1-27B ships with 27B parameters. Total weight footprint is approximately 27.8 GB, which is the relevant figure when planning local-inference VRAM. Distribution is governed by the cc license — review the exact terms before commercial deployment.
Reasoning-Medical0.1-27B is best fit for mixed text-and-image reasoning tasks such as document understanding. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
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arXiv:2610.28176v1 Announce Type: cross Abstract: Large Language Models (LLMs) often struggle with temporally grounded reasoning because their static parametric memory is misaligned with the dynamic evolution of real-world knowledge. Although RAG and Parameter-Efficient Fine-Tuning (PEFT) provide pr
The Culture Within: Towards Mechanistic Understanding of Cultural Reasoning in LLMs
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arXiv:2610.28584v1 Announce Type: new Abstract: Autoregressive models (ARMs) face a "Sequentiality Bottleneck" in reasoning, while diffusion language models (DLMs) offer parallelism but lack semantic coherence. To addresses both limitations, we propose Collaborative Reasoning Asymmetric Learning (Co
S-Agent 2.0: Spatial Reasoning with a General Coding Agent
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Perceives but Doesn't Brake: A Perception-Action Binding Gap in Reasoning Driving VLAs
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