100 citations · 183 across the 23 of their papers we have counts for
3 papers · 2 filters
Universal Vision-Language Dense Retrieval: Learning A Unified Representation Space for Multi-Modal Retrieval
Zhenghao Liu, Chenyan Xiong, Yuanhuiyi Lv +2
This paper presents Universal Vision-Language Dense Retrieval (UniVL-DR), which builds a unified model for multi-modal retrieval. UniVL-DR encodes queries and multi-modality resour…
P^3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-based Learning and Pre-finetuning
Xiaomeng Hu, Shi Yu, Chenyan Xiong +3
Compared to other language tasks, applying pre-trained language models (PLMs) for search ranking often requires more nuances and training signals. In this paper, we identify and st…
Dimension Reduction for Efficient Dense Retrieval via Conditional Autoencoder
Zhenghao Liu, Han Zhang, Chenyan Xiong +3
Dense retrievers encode queries and documents and map them in an embedding space using pre-trained language models. These embeddings need to be high-dimensional to fit training sig…