2 citations · 3 across the 5 of their papers we have counts for
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cs.LG2026
IRIS: Implicit Reward-Guided Internal Sifting for Mitigating Multimodal Hallucination
Yuanshuai Li, Yuping Yan, Jirui Han +3
Hallucination remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While Direct Preference Optimization (DPO) is a key alignment framework, existing approa…
cs.LG2023★ 2 cited
TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation
Jie Zhang, Chen Chen, Weiming Zhuang +1
This paper focuses on an under-explored yet important problem: Federated Class-Continual Learning (FCCL), where new classes are dynamically added in federated learning. Existing FC…
cs.LG2022★ 1 cited
sqSGD: Locally Private and Communication Efficient Federated Learning
Yan Feng, Tao Xiong, Ruofan Wu +2
Federated learning (FL) is a technique that trains machine learning models from decentralized data sources. We study FL under local notions of privacy constraints, which provides s…