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2024 ICML ICML 2024

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian R. Bartoldson, Ajay Kumar Jaiswal, Kaidi Xu, Bhavya Kailkhura, Dan Hendrycks, Dawn Song, Zhangyang Wang, Bo Li

Topics

Artificial Intelligence > Core AI > Model Compression Artificial Intelligence > Core AI > Responsible AI Artificial Intelligence > Core AI > Large Language Models

Keywords

quantization fairness pruning trustworthiness bit levels ethics
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