collaborators

13 papers

astro-ph.IM2026

Voltage-to-temperature calibration of the High Altitude THz Solar telescope acquisition system

Gedeane G. S. Kenshima, Daniel R. Sousa, Tiago Giorgetti +2

The THz range has been under-explored for solar astronomy, mainly due to technological limitations. Only recently, a few new telescopes, such as the High Altitude Terahertz Solar (…

cs.LG2026

Sketched Linear Contrastive Learning: Approximation, Optimization, and Statistical Scaling

Ziyan Chen, Zhongzhu Zhou, Ding-Xuan Zhou

Scaling laws describe how learning performance varies with model size, data size, and compute. While recent theoretical work has established scaling laws for sketched linear regres…

cs.LG2026

Taylor-Calibrate: Principled Initialization for Hybrid Linear Attention Distillation

Zhongzhu Zhou, Qingyang Wu, Junxiong Wang +4

Hybrid linear attention models offer an appealing path to faster long-context inference: they reduce the quadratic cost and KV-cache burden of full softmax attention while retainin…

cs.LG2026

OSCAR: Offline Spectral Covariance-Aware Rotation for 2-bit KV Cache Quantization

Zhongzhu Zhou, Donglin Zhuang, Jisen Li +4

INT2 KV-cache quantization is attractive for long-context LLM serving, but it remains difficult to make both accurate and deployable. Simple rotations such as Hadamard transforms r…

cs.LG2026

When RL Meets Adaptive Speculative Training: A Unified Training-Serving System

Junxiong Wang, Fengxiang Bie, Jisen Li +14

Speculative decoding can significantly accelerate LLM serving, yet most deployments today disentangle speculator training from serving, treating speculator training as a standalone…

cs.LG2026

SAW-INT4: System-Aware 4-Bit KV-Cache Quantization for Real-World LLM Serving

Jinda Jia, Jisen Li, Zhongzhu Zhou +8

KV-cache memory is a major bottleneck in real-world LLM serving, where systems must simultaneously support latency-sensitive small-batch requests and high-throughput concurrent wor…