46 citations · 47 across the 3 of their papers we have counts for
3 papers
cs.CV2025
Learn 3D VQA Better with Active Selection and Reannotation
Shengli Zhou, Yang Liu, Feng Zheng
3D Visual Question Answering (3D VQA) is crucial for enabling models to perceive the physical world and perform spatial reasoning. In 3D VQA, the free-form nature of answers often…
cs.LG2024★ 1 cited
Adversarial Machine Unlearning
Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik +1
This paper focuses on the challenge of machine unlearning, aiming to remove the influence of specific training data on machine learning models. Traditionally, the development of un…
cs.LG2016★ 46 cited
Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening
Frank S. He, Yang Liu, Alexander G. Schwing +1
We propose a novel training algorithm for reinforcement learning which combines the strength of deep Q-learning with a constrained optimization approach to tighten optimality and e…