1 citations · 2 across the 6 of their papers we have counts for
6 papers
Expanding-and-Shrinking Binary Neural Networks
Xulong Shi, Caiyi Sun, Zhi Qi +2
While binary neural networks (BNNs) offer significant benefits in terms of speed, memory and energy, they encounter substantial accuracy degradation in challenging tasks compared t…
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
Marianne Arriola, Aaron Gokaslan, Justin T. Chiu +5
Diffusion language models offer unique benefits over autoregressive models due to their potential for parallelized generation and controllability, yet they lag in likelihood modeli…
Improving Decoupled Posterior Sampling for Inverse Problems using Data Consistency Constraint
Zhi Qi, Shihong Yuan, Yulin Yuan +3
Diffusion models have shown strong performances in solving inverse problems through posterior sampling while they suffer from errors during earlier steps. To mitigate this issue, s…
Adaptive Adapter Routing for Long-Tailed Class-Incremental Learning
Zhi-Hong Qi, Da-Wei Zhou, Yiran Yao +2
In our ever-evolving world, new data exhibits a long-tailed distribution, such as e-commerce platform reviews. This necessitates continuous model learning imbalanced data without f…
TV100: A TV Series Dataset that Pre-Trained CLIP Has Not Seen
Da-Wei Zhou, Zhi-Hong Qi, Han-Jia Ye +1
The era of pre-trained models has ushered in a wealth of new insights for the machine learning community. Among the myriad of questions that arise, one of paramount importance is:…
Eyes on the Streets: Leveraging Street-Level Imaging to Model Urban Crime Dynamics
Zhixuan Qi, Huaiying Luo, Chen Chi
This study addresses the challenge of urban safety in New York City by examining the relationship between the built environment and crime rates using machine learning and a compreh…