4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 4 cited
Higher Layers Need More LoRA Experts
Chongyang Gao, Kezhen Chen, Jinmeng Rao +7
Parameter-efficient tuning (PEFT) techniques like low-rank adaptation (LoRA) offer training efficiency on Large Language Models, but their impact on model performance remains limit…
cs.CL2023★ 1 cited
Tackling Vision Language Tasks Through Learning Inner Monologues
Diji Yang, Kezhen Chen, Jinmeng Rao +4
Visual language tasks require AI models to comprehend and reason with both visual and textual content. Driven by the power of Large Language Models (LLMs), two prominent methods ha…
cs.CV2023
LOWA: Localize Objects in the Wild with Attributes
Xiaoyuan Guo, Kezhen Chen, Jinmeng Rao +3
We present LOWA, a novel method for localizing objects with attributes effectively in the wild. It aims to address the insufficiency of current open-vocabulary object detectors, wh…