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From the 2 of 17 linked papers with an AI index.

collaborators

17 papers

cs.AI2026

FOCUS: FP4 Optimization via Coupled-Relaxation and Dual-Granularity Scaling

Xianglong Yan, Hong Liu, Chengzhu Bao +4

Large language models (LLMs) achieve remarkable performance but are expensive to deploy due to their enormous size. FP4 quantization, with formats such as MXFP4 and NVFP4, offers a…

cs.CL2026

AngelSpec: Towards Real-World High Performance Inference with Speculative Decoding

Hong Liu, Rui Cen, Junhan Shi +10

Speculative decoding accelerates large language model inference without changing the target distribution, but no single drafting structure performs best across real-world workloads…

cs.CL2026

CoSA: Accelerating Long-Context Inference via Proxy-Kernel Co-Designed Sparse Attention

Yufei Xue, Lin Niu, Hong Liu +6

CoSA introduces a training-free, two-stage sparse attention method that jointly designs a proxy and kernel to efficiently handle very long contexts, achieving faster inference with…

cs.CL2026

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention

Hong Liu, Yuan Cheng, Lin Niu +5

Token-level sparse attention, as implemented by DeepSeek Sparse Attention (DSA) in production systems, makes the downstream attention efficient but shifts the bottleneck to the ind…

cs.CL2026

D-cut: Adaptive Verification Depth Pruning for Batched Speculative Decoding

Tianyu Liu, Yuhao Shen, Rui Cen +7

The paper introduces D-Cut, an adaptive method that prunes draft tokens across a batch to focus verification on the most promising tokens, improving the speed of speculative decodi…

cs.CV2026

HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better

Gengluo Li, Xingyu Wan, Shangpin Peng +20

We present HunyuanOCR-1.5, a lightweight end-to-end OCR-specialized vision-language model. HunyuanOCR unifies document parsing, text spotting, information extraction, text-image tr…