most citedMiMo-Audio: Audio Language Models are Few-Shot Learners

2 citations · 4 across the 8 of their papers we have counts for

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cs.CL2026

SpeechParaling-Bench: A Comprehensive Benchmark for Paralinguistic-Aware Speech Generation

Ruohan Liu, Shukang Yin, Tao Wang +6

Paralinguistic cues are essential for natural human-computer interaction, yet their evaluation in Large Audio-Language Models (LALMs) remains limited by coarse feature coverage and…

cs.CL2026

OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Models

Han Zhu, Lingxuan Ye, Wei Kang +7

We present OmniVoice, a massively multilingual zero-shot text-to-speech (TTS) model that scales to over 600 languages. At its core is a novel diffusion language model-style discret…

cs.CL2026★ 1 cited

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★ 2 cited

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★ 1 cited

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…

cs.CL2025

MiMo-VL Technical Report

Core Team, Zihao Yue, Zhenru Lin +71

We open-source MiMo-VL-7B-SFT and MiMo-VL-7B-RL, two powerful vision-language models delivering state-of-the-art performance in both general visual understanding and multimodal rea…