2 citations · 6 across the 7 of their papers we have counts for
9 papers
Swordsman: Entropy-Driven Adaptive Block Partition for Efficient Diffusion Language Models
Yu Zhang, Xinchen Li, Jialei Zhou +6
Block-wise decoding effectively improves the inference speed and quality in diffusion language models (DLMs) by combining inter-block sequential denoising and intra-block parallel…
Adaptive Visual Autoregressive Acceleration via Dual-Linkage Entropy Analysis
Yu Zhang, Jingyi Liu, Feng Liu +5
Visual AutoRegressive modeling (VAR) suffers from substantial computational cost due to the massive token count involved. Failing to account for the continuous evolution of modelin…
Markovian Scale Prediction: A New Era of Visual Autoregressive Generation
Yu Zhang, Jingyi Liu, Yiwei Shi +4
Visual AutoRegressive modeling (VAR) based on next-scale prediction has revitalized autoregressive visual generation. Although its full-context dependency, i.e., modeling all previ…
Revealing Multimodal Causality with Large Language Models
Jin Li, Shoujin Wang, Qi Zhang +5
Uncovering cause-and-effect mechanisms from data is fundamental to scientific progress. While large language models (LLMs) show promise for enhancing causal discovery (CD) from uns…
Enhancing Text-to-Image Diffusion Transformer via Split-Text Conditioning
Yu Zhang, Jialei Zhou, Xinchen Li +6
Current text-to-image diffusion generation typically employs complete-text conditioning. Due to the intricate syntax, diffusion transformers (DiTs) inherently suffer from a compreh…
Graph Memory Learning: Imitating Lifelong Remembering and Forgetting of Brain Networks
Jiaxing Miao, Liang Hu, Qi Zhang +1
Graph data in real-world scenarios undergo rapid and frequent changes, making it challenging for existing graph models to effectively handle the continuous influx of new data and a…
Causal Learning for Trustworthy Recommender Systems: A Survey
Jin Li, Shoujin Wang, Qi Zhang +5
Recommender Systems (RS) have significantly advanced online content filtering and personalized decision-making. However, emerging vulnerabilities in RS have catalyzed a paradigm sh…
DE-BERT: Distance-Enhanced Early Exiting for BERT based on Prototypical Networks
Jianing He, Qi Zhang, Weiping Ding +4
Early exiting has demonstrated its effectiveness in accelerating the inference of pre-trained language models like BERT by dynamically adjusting the number of layers executed. Howe…
Frequency Spectrum is More Effective for Multimodal Representation and Fusion: A Multimodal Spectrum Rumor Detector
An Lao, Qi Zhang, Chongyang Shi +4
Multimodal content, such as mixing text with images, presents significant challenges to rumor detection in social media. Existing multimodal rumor detection has focused on mixing t…