Author

Jin-Bao Xue

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#artificial intelligence Preprint Sep 2026

Calibrate the Decisions That Change the Future: On-Policy Post-Training Quantization for Multimodal Large Language Models

Post-training quantization (PTQ) lowers deployment cost for multimodal large language models, but calibration typically reconstructs fixed sequences with local objectives. This overlooks autoregressive feedback: a quantization-induced token change redirects the prefix and changes future states. Yet on-policy coverage a...

Wen-Xiao Fan, Jing-Ling Fu, Li-Chen Ma et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Hunyuan-A13B Technical Report

We present Hunyuan-A13B, an open-source large language model based on a Mixture-of-Experts architecture. It contains 80 billion total parameters but activates only 13 billion during inference, balancing model capability, computational efficiency, and deployment cost. The model is pretrained on a rigorously filtered 20T...

Tencent Hunyuan Team, Ao Liu, Bo Zhou et al. · 0 citations