6 citations · 7 across the 5 of their papers we have counts for
5 papers
Panoptic Diffusion Models: co-generation of images and segmentation maps
Yinghan Long, Kaushik Roy
Recently, diffusion models have demonstrated impressive capabilities in text-guided and image-conditioned image generation. However, existing diffusion models cannot simultaneously…
Prompt-Based Bias Calibration for Better Zero/Few-Shot Learning of Language Models
Kang He, Yinghan Long, Kaushik Roy
Prompt-based learning is susceptible to intrinsic bias present in pre-trained language models (LMs), leading to sub-optimal performance in prompt-based zero/few-shot settings. In t…
Segmented Recurrent Transformer: An Efficient Sequence-to-Sequence Model
Yinghan Long, Sayeed Shafayet Chowdhury, Kaushik Roy
Transformers have shown dominant performance across a range of domains including language and vision. However, their computational cost grows quadratically with the sequence length…
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems
Yinghan Long, Indranil Chakraborty, Gopalakrishnan Srinivasan +1
The ubiquitous use of IoT and machine learning applications is creating large amounts of data that require accurate and real-time processing. Although edge-based smart data process…
Conditionally Deep Hybrid Neural Networks Across Edge and Cloud
Yinghan Long, Indranil Chakraborty, Kaushik Roy
The pervasiveness of "Internet-of-Things" in our daily life has led to a recent surge in fog computing, encompassing a collaboration of cloud computing and edge intelligence. To th…