37 citations · 93 across the 9 of their papers we have counts for
Showing 2023 · cs.CLShow all
3 papers · 2 filters
cs.CL2023
Noisy Pair Corrector for Dense Retrieval
Hang Zhang, Yeyun Gong, Xingwei He +4
Most dense retrieval models contain an implicit assumption: the training query-document pairs are exactly matched. Since it is expensive to annotate the corpus manually, training p…
cs.CL2023★ 18 cited
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
Hang Zhang, Xin Li, Lidong Bing
We present Video-LLaMA a multi-modal framework that empowers Large Language Models (LLMs) with the capability of understanding both visual and auditory content in the video. Video-…
cs.CL2023★ 34 cited
AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators
Xingwei He, Zhenghao Lin, Yeyun Gong +7
Many natural language processing (NLP) tasks rely on labeled data to train machine learning models with high performance. However, data annotation is time-consuming and expensive,…