15 citations · 27 across the 7 of their papers we have counts for
9 papers
Polyhistor: Parameter-Efficient Multi-Task Adaptation for Dense Vision Tasks
Yen-Cheng Liu, Chih-Yao Ma, Junjiao Tian +2
Adapting large-scale pretrained models to various downstream tasks via fine-tuning is a standard method in machine learning. Recently, parameter-efficient fine-tuning methods show…
FedFOR: Stateless Heterogeneous Federated Learning with First-Order Regularization
Junjiao Tian, James Seale Smith, Zsolt Kira
Federated Learning (FL) seeks to distribute model training across local clients without collecting data in a centralized data-center, hence removing data-privacy concerns. A major…
Overcoming Obstructions via Bandwidth-Limited Multi-Agent Spatial Handshaking
Nathaniel Glaser, Yen-Cheng Liu, Junjiao Tian +1
In this paper, we address bandwidth-limited and obstruction-prone collaborative perception, specifically in the context of multi-agent semantic segmentation. This setting presents…
Enhancing Multi-Robot Perception via Learned Data Association
Nathaniel Glaser, Yen-Cheng Liu, Junjiao Tian +1
In this paper, we address the multi-robot collaborative perception problem, specifically in the context of multi-view infilling for distributed semantic segmentation. This setting…
Posterior Re-calibration for Imbalanced Datasets
Junjiao Tian, Yen-Cheng Liu, Nathan Glaser +2
Neural Networks can perform poorly when the training label distribution is heavily imbalanced, as well as when the testing data differs from the training distribution. In order to…
Image Captioning with Compositional Neural Module Networks
Junjiao Tian, Jean Oh
In image captioning where fluency is an important factor in evaluation, e.g., -gram metrics, sequential models are commonly used; however, sequential models generally result in…