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From the 1 of 7 linked papers with an AI index.

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7 papers

cs.AI2026

Beyond Rephrasing: Book-Level Organization Improves Synthetic Textbook Data for Mid-Training

Jiawen Tao, Miao Peng, Yaoming Li +7

The paper introduces a pipeline that creates synthetic textbooks by clustering source material, planning hierarchical tables of contents, and assembling sections into full books, s…

cs.CL2026

MedAction: Towards Active Multi-turn Clinical Diagnostic LLMs

Hsin-Ling Hsu, Zizheng Wang, Donghua Zhang +9

Most existing LLM diagnoses are evaluated on static, single-turn settings where complete patient information is provided upfront, an oversimplification of real clinical practice. W…

eess.SP2026

NeuroNarrator: A Generalist EEG-to-Text Foundation Model for Clinical Interpretation via Spectro-Spatial Grounding and Temporal State-Space Reasoning

Guoan Wang, Shihao Yang, Jun-en Ding +2

Electroencephalography (EEG) provides a non-invasive window into neural dynamics at high temporal resolution and plays a pivotal role in clinical neuroscience research. Despite thi…

cs.CL2026

MiMo-V2-Flash Technical Report

Core Team, Bangjun Xiao, Bingquan Xia +123

We present MiMo-V2-Flash, a Mixture-of-Experts (MoE) model with 309B total parameters and 15B active parameters, designed for fast, strong reasoning and agentic capabilities. MiMo-…

cs.CL2025

MiMo-Audio: Audio Language Models are Few-Shot Learners

Core Team, Dong Zhang, Gang Wang +97

Existing audio language models typically rely on task-specific fine-tuning to accomplish particular audio tasks. In contrast, humans are able to generalize to new audio tasks with…

cs.CL2025

MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining

LLM-Core Xiaomi, :, Bingquan Xia +62

We present MiMo-7B, a large language model born for reasoning tasks, with optimization across both pre-training and post-training stages. During pre-training, we enhance the data p…