Causal reasoning meets visual representation learning: A prospective study

Y Liu, YS Wei, H Yan, GB Li, L Lin - Machine Intelligence Research, 2022 - Springer
Visual representation learning is ubiquitous in various real-world applications, including
visual comprehension, video understanding, multi-modal analysis, human-computer …

[HTML][HTML] GPT understands, too

X Liu, Y Zheng, Z Du, M Ding, Y Qian, Z Yang, J Tang - AI Open, 2024 - Elsevier
Prompting a pretrained language model with natural language patterns has been proved
effective for natural language understanding (NLU). However, our preliminary study reveals …

Causal machine learning: A survey and open problems

J Kaddour, A Lynch, Q Liu, MJ Kusner… - ar** the good and removing the bad momentum causal effect
K Tang, J Huang, H Zhang - Advances in neural information …, 2020 - proceedings.neurips.cc
As the class size grows, maintaining a balanced dataset across many classes is challenging
because the data are long-tailed in nature; it is even impossible when the sample-of-interest …

Causal intervention for weakly-supervised semantic segmentation

D Zhang, H Zhang, J Tang… - Advances in neural …, 2020 - proceedings.neurips.cc
We present a causal inference framework to improve Weakly-Supervised Semantic
Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by …

Cross-modal causal relational reasoning for event-level visual question answering

Y Liu, G Li, L Lin - IEEE Transactions on Pattern Analysis and …, 2023 - ieeexplore.ieee.org
Existing visual question answering methods often suffer from cross-modal spurious
correlations and oversimplified event-level reasoning processes that fail to capture event …