73 citations · 519 across the 19 of their papers we have counts for
5 papers · 1 filter
RHS-TRNG: A Resilient High-Speed True Random Number Generator Based on STT-MTJ Device
Siqing Fu, Tiejun Li, Chunyuan Zhang +5
High-quality random numbers are very critical to many fields such as cryptography, finance, and scientific simulation, which calls for the design of reliable true random number gen…
Bias and Fairness in Large Language Models: A Survey
Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow +6
Rapid advancements of large language models (LLMs) have enabled the processing, understanding, and generation of human-like text, with increasing integration into systems that touc…
LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding
Yanzhe Zhang, Ruiyi Zhang, Jiuxiang Gu +4
Instruction tuning unlocks the superior capability of Large Language Models (LLM) to interact with humans. Furthermore, recent instruction-following datasets include images as visu…
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels
Jian Chen, Ruiyi Zhang, Tong Yu +4
Learning from noisy labels is an important and long-standing problem in machine learning for real applications. One of the main research lines focuses on learning a label corrector…
Towards Building the Federated GPT: Federated Instruction Tuning
Jianyi Zhang, Saeed Vahidian, Martin Kuo +6
While "instruction-tuned" generative large language models (LLMs) have demonstrated an impressive ability to generalize to new tasks, the training phases heavily rely on large amou…