12 citations · 20 across the 6 of their papers we have counts for
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cs.LG2024★ 1 cited
Beyond Accuracy: Ensuring Correct Predictions With Correct Rationales
Tang Li, Mengmeng Ma, Xi Peng
Large pretrained foundation models demonstrate exceptional performance and, in some high-stakes applications, even surpass human experts. However, most of these models are currentl…
cs.LG2024
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
Mengmeng Ma, Tang Li, Xi Peng
Federated Learning is widely employed to tackle distributed sensitive data. Existing methods primarily focus on addressing in-federation data heterogeneity. However, we observed th…
cs.LG2023★ 2 cited
Are Data-driven Explanations Robust against Out-of-distribution Data?
Tang Li, Fengchun Qiao, Mengmeng Ma +1
As black-box models increasingly power high-stakes applications, a variety of data-driven explanation methods have been introduced. Meanwhile, machine learning models are constantl…