activity
20202025
most citedDefense of Word-level Adversarial Attacks via Random Substitution Encoding

5 citations · 5 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Verifiable Format Control for Large Language Model Generations

Zhaoyang Wang, Jinqi Jiang, Huichi Zhou +4

Recent Large Language Models (LLMs) have demonstrated satisfying general instruction following ability. However, small LLMs with about 7B parameters still struggle fine-grained for…

cs.LG2024

CREAM: Consistency Regularized Self-Rewarding Language Models

Zhaoyang Wang, Weilei He, Zhiyuan Liang +5

Recent self-rewarding large language models (LLM) have successfully applied LLM-as-a-Judge to iteratively improve the alignment performance without the need of human annotations fo…

cs.CV2024

Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement

Xiyao Wang, Jiuhai Chen, Zhaoyang Wang +8

Large vision-language models (LVLMs) have achieved impressive results in visual question-answering and reasoning tasks through vision instruction tuning on specific datasets. Howev…

cs.CL2023

Democratizing Reasoning Ability: Tailored Learning from Large Language Model

Zhaoyang Wang, Shaohan Huang, Yuxuan Liu +8

Large language models (LLMs) exhibit impressive emergent abilities in natural language processing, but their democratization is hindered due to huge computation requirements and cl…

cs.CL20205 cited

Defense of Word-level Adversarial Attacks via Random Substitution Encoding

Zhaoyang Wang, Hongtao Wang

The adversarial attacks against deep neural networks on computer vision tasks have spawned many new technologies that help protect models from avoiding false predictions. Recently,…