14 citations · 25 across the 6 of their papers we have counts for
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cs.CV2023
Mitigating Task Interference in Multi-Task Learning via Explicit Task Routing with Non-Learnable Primitives
Chuntao Ding, Zhichao Lu, Shangguang Wang +2
Multi-task learning (MTL) seeks to learn a single model to accomplish multiple tasks by leveraging shared information among the tasks. Existing MTL models, however, have been known…
cs.LG2023★ 10 cited
Rethinking Population-assisted Off-policy Reinforcement Learning
Bowen Zheng, Ran Cheng
While off-policy reinforcement learning (RL) algorithms are sample efficient due to gradient-based updates and data reuse in the replay buffer, they struggle with convergence to lo…