arXiv AI By Zhixiong Zhao, Zukang Xu, Xing Hu, Lifeng Liu, Guangyu Sun, Dawei Yang

LoopQuant: Accurate and Efficient Post-Training Quantization for Looped Transformers

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arXiv Machine Learning
Oct 8

ResidualQuant: KV Cache Quantization for Looped Transformers with 2-Bit Residuals

ResidualQuant introduces a 2‑bit residual quantization scheme for KV caches in looped Transformers, leveraging the similarity of KV states across loops. By using the final‑loop KV states as a reference and applying least‑square scaling, rotations, and loop‑wise mixed precision, the method achieves accurate quantization down to INT2. Experiments on various looped Transformer models show that ResidualQuant improves the accuracy‑memory tradeoff, retaining near BF16 accuracy while reducing KV storage by 80.7% and boosting decode throughput and batch size on an RTX 5090.

By Heejun Kim, Junyoung Lee, SangLyul Cho, Dongsu Han, Insu Han, Sehoon Kim
arXiv Machine Learning
Sep 25

FlashLoop: Fast and Memory-Efficient Looped Transformers via Lazy Updates

FlashLoop is a training‑free inference framework for Looped Transformers that reduces cross‑loop redundancy by employing token‑sparse updates, sparse attention, and KV‑residual quantization. It exploits observations that, as loops progress, state changes concentrate on a small token subset, attention differences are dominated by a sparse key subset, and KV residuals become amenable to low‑bit quantization. The method achieves lossless accuracy with up to 1.64× speedup and 6× KV‑cache memory reduction across several Looped Transformer models.

By Wanqi Yang, Shiwei Liu
arXiv AI
Sep 30

LeapQuant: Efficient Linear Attention with Accurate Recurrent State Quantization

arXiv:2609.38166v1 Announce Type: cross Abstract: Recent LLMs increasingly adopt hybrid designs that replace standard attention with linear attention, such as Gated DeltaNet (GDN) and Kimi Delta Atte...

By Yi Pan, Haocheng Xi, Kan Zhu, Xingyang Li, Yibo Wu, Mayank Mishra, Hongtao Zhang, William X. Zheng, Baris Kasikci, Song Han, Kurt Keutzer, Rishabh Iyer, Ion Stoica