1 citations · 2 across the 10 of their papers we have counts for
12 papers
The Functional Structure of Post-Compression Recovery in Low-Rank LLMs
Zishan Shao, Liang Tian, Georgiy Zemlevskiy +10
Different low-rank compression methods can produce compressed LLMs that respond differently to the same post-compression recovery procedure, and relative advantages observed betwee…
Joint Branch-Space Transform Coding for Diffusion Activation Quantization with Classifier-Free Guidance
Mingrun Jiang, Yuejia Liu, Zishan Shao +11
Post-training quantization for diffusion models increasingly exploits timestep, feature, and layer structure. While recent work has begun incorporating CFG structure into diffusion…
LowRankArena: A Standardized Evaluation Platform for SVD-Based LLM Compression
Zishan Shao, Lixun Zhang, Kangning Cui +10
SVD-based low-rank compression has become a fast-growing direction for reducing the memory and computational cost of large language models (LLMs). However, meaningful comparison ac…
DecodeShare: Tracing the Shared Subspace of LLM Decode-Time Decisions
Zishan Shao, Lixun Zhang, Kangning Cui +10
Large language models (LLMs) handle many tasks with one set of parameters, but under KV-cached inference it is unclear what task-general structure, if any, is used at decode time r…
Beyond Text Prompts: Visual-to-Visual Generation as A Unified Paradigm
Yaofang Liu, Kangning Cui, Meng Chu +7
Humans often specify and create through visual artifacts: typography sheets, sketches, reference images, and annotated scenes. Yet modern visual generators still ask users to seria…
FlashSVD v1.5: Making Low-Rank Transformers Inference Actually Fast
Wenhao Wu, Zishan Shao, Kangning Cui +5
SVD-based Low-rank compression reduces transformer parameters and nominal FLOPs, but these savings often translate poorly into real LLM serving speedups. We show that this gap is l…
Learning Where to Embed: Noise-Aware Positional Embedding for Query Retrieval in Small-Object Detection
Yangchen Zeng, Zhenyu Yu, Dongming Jiang +5
Transformer-based detectors have advanced small-object detection, but they often remain inefficient and vulnerable to background-induced query noise, which motivates deep decoders…
SphUnc: Hyperspherical Uncertainty Decomposition and Causal Identification via Information Geometry
Rong Fu, Chunlei Meng, Jinshuo Liu +8
Reliable decision-making in complex multi-agent systems requires calibrated predictions and interpretable uncertainty. We introduce SphUnc, a unified framework combining hyperspher…
StoryState: Agent-Based State Control for Consistent and Editable Storybooks
Ayushman Sarkar, Zhenyu Yu, Wei Tang +3
Large multimodal models have enabled one-click storybook generation, where users provide a short description and receive a multi-page illustrated story. However, the underlying sto…
ReDiStory: Region-Disentangled Diffusion for Consistent Visual Story Generation
Ayushman Sarkar, Zhenyu Yu, Chu Chen +3
Generating coherent visual stories requires maintaining subject identity across multiple images while preserving frame-specific semantics. Recent training-free methods concatenate…
MoSAiC: Multi-Modal Multi-Label Supervision-Aware Contrastive Learning for Remote Sensing
Debashis Gupta, Aditi Golder, Rongkhun Zhu +6
Contrastive learning (CL) has emerged as a powerful paradigm for learning transferable representations without the reliance on large labeled datasets. Its ability to capture intrin…
Center-guided Classifier for Semantic Segmentation of Remote Sensing Images
Wei Zhang, Mengting Ma, Yizhen Jiang +4
Compared with natural images, remote sensing images (RSIs) have the unique characteristic. i.e., larger intraclass variance, which makes semantic segmentation for remote sensing im…