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Haoli Bai

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#machine learning Preprint Sep 2026

PQ-HSA: Reusing Product-Quantized Scores for Hybrid Sparse-Approximate Attention

At each decoding step a language model attends over the key-value (KV) cache of every earlier token, so at long context the attention call is bounded by memory bandwidth. Sparse attention reads only a subset of keys chosen by a cheap score estimate, and most methods give the unread tokens zero weight. The output then d...

Kun-Ming Shao, Jie-Run Chen, Yan-Li Wang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

G$^2$PTQ: Improving LLM Post-Training Quantization with Generalized Gradient Compensation

G$^2$PTQ is presented, a unified PTQ framework with Generalized Gradient Compensation that integrates both first- and second-order information under a globally supervised, block-wise optimization objective and enables better alignment with the full-precision model, outperforming state-of-the-art baselines.

Rui-Kang Liu, Hao-Li Bai, Yuxuan Sun et al. · 0 citations
Preprint Jul 2026

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget

We introduce Boogu-Image-0.1, an open-source unified multimodal understanding and generation model family, comprising Base, Turbo, Edit, and Edit-Turbo variants. It delivers competitive performance in high-quality text-to-image generation, fast inference, instruction-based editing, and bilingual (Chinese-English) text...

Guoxuan Chen, Chufeng Xiao, Haoran Yang et al. · 1 citation
Preprint Aug 2026

AdaMTP: An Adaptive Training Paradigm for Multi-Token Prediction

AdaMTP is proposed, an adaptive training paradigm that dynamically aligns the prediction horizon with the intrinsic predictability of the sequence, and consistently outperforms standard MTP in both task performance and inference speedup.

Ziqiang Cui, Han Shi, Bowei He et al. · 0 citations

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