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cs.LG2026
Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks
Miaomiao Li, Hao Chen, Yang Wang +5
Generating synthetic datasets via large language models (LLMs) has emerged as a promising approach to improve LLM performance. However, LLMs inherently reflect biases in their trai…
cs.LG2024
On Catastrophic Inheritance of Large Foundation Models
Hao Chen, Bhiksha Raj, Xing Xie +1
Large foundation models (LFMs) are claiming incredible performances. Yet great concerns have been raised about their mythic and uninterpreted potentials not only in machine learnin…
cs.LG2024
A General Framework for Learning from Weak Supervision
Hao Chen, Jindong Wang, Lei Feng +6
Weakly supervised learning generally faces challenges in applicability to various scenarios with diverse weak supervision and in scalability due to the complexity of existing algor…