activity
20192023
most citedBeneficial Perturbation Network for designing general adaptive artificial intelligence systems

18 citations · 45 across the 16 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CV2023★ 3 cited

Beyond Generation: Harnessing Text to Image Models for Object Detection and Segmentation

Yunhao Ge, Jiashu Xu, Brian Nlong Zhao +3

We propose a new paradigm to automatically generate training data with accurate labels at scale using the text-to-image synthesis frameworks (e.g., DALL-E, Stable Diffusion, etc.).…

cs.CV2023★ 1 cited

CLR: Channel-wise Lightweight Reprogramming for Continual Learning

Yunhao Ge, Yuecheng Li, Shuo Ni +3

Continual learning aims to emulate the human ability to continually accumulate knowledge over sequential tasks. The main challenge is to maintain performance on previously learned…

cs.CV2023

Robustness Analysis on Foundational Segmentation Models

Madeline Chantry Schiappa, Shehreen Azad, Sachidanand VS +4

Due to the increase in computational resources and accessibility of data, an increase in large, deep learning models trained on copious amounts of multi-modal data using self-super…

cs.CV2023★ 1 cited

Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD Detection Using Text-image Models

Yunhao Ge, Jie Ren, Jiaping Zhao +4

We focus on the challenge of out-of-distribution (OOD) detection in deep learning models, a crucial aspect in ensuring reliability. Despite considerable effort, the problem remains…

cs.LG2023★ 6 cited

Lightweight Learner for Shared Knowledge Lifelong Learning

Yunhao Ge, Yuecheng Li, Di Wu +12

In Lifelong Learning (LL), agents continually learn as they encounter new conditions and tasks. Most current LL is limited to a single agent that learns tasks sequentially. Dedicat…