11 citations · 11 across the 9 of their papers we have counts for
10 papers
RA-CFGCache: From Branch-Level Criteria to Guided-Risk Control under Classifier-Free Guidance
Yiming Liu, Ben Wan, Tongxuan Liu +5
Diffusion models enable high-quality visual generation, but iterative denoising remains computationally expensive, especially under classifier-free guidance (CFG), which requires b…
PosterText: Towards Unified Visual Text Generation and Editing for E-commerce Poster
Xiaoan Liu, Lichen Ma, Zipeng Guo +12
Automated e-commerce poster design requires both high-quality poster generation and flexible editing of existing designs. However, most existing methods either target end-to-end po…
iFAN: Inference-Aware Learning for Plain Mask Transformers
Fang Li, Yu He, Haoyang Tong +7
Query-based mask transformers assemble segmentation outputs through pixel-wise competition among query predictions of the final layer, yet this inference process is not explicitly…
BLADE: Scalable Bi-level Adaptive Data Selection for LLM Training
Jiaxing Wang, Deping Xiang, Jin Xu +9
As Large Language Model (LLM) datasets scale to trillions of tokens, data selection has emerged as a critical frontier to filter out uninformative noise and construct adaptive lear…
FastOCR: Dynamic Visual Fixation via KV Cache Pruning for Efficient Document Parsing
Zihan Tang, Leqi Shen, Hui Chen +7
Vision-Language Models (VLMs) have shown strong promise on Optical Character Recognition (OCR), yet the sheer number of visual tokens required to encode dense documents incurs proh…
MISA: Mixture of Indexer Sparse Attention for Long-Context LLM Inference
Ruijie Zhou, Fanxu Meng, Yufei Xu +4
DeepSeek Sparse Attention (DSA) sets the state of the art for fine-grained inference-time sparse attention by introducing a learned token-wise indexer that scores every prefix toke…
HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention
Yufei Xu, Fanxu Meng, Fan Jiang +11
Token-level sparse attention mechanisms, exemplified by DeepSeek Sparse Attention (DSA), achieve fine-grained key selection by scoring every historical key for each query through a…
xGR: Efficient Generative Recommendation Serving at Scale
Qingxiao Sun, Tongxuan Liu, Shen Zhang +13
Recommendation system delivers substantial economic benefits by providing personalized predictions. Generative recommendation (GR) integrates LLMs to enhance the understanding of l…
Minions: Accelerating Large Language Model Inference with Aggregated Speculative Execution
Siqi Wang, Hailong Yang, Xuezhu Wang +10
Large language models (LLM) have recently attracted surging interest due to their outstanding capabilities across various domains. However, enabling efficient LLM inference is chal…
MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions
Wenqi Jiang, Zhenhao He, Shuai Zhang +9
Deep neural networks are widely used in personalized recommendation systems. Unlike regular DNN inference workloads, recommendation inference is memory-bound due to the many random…