Bridging language and items for retrieval and recommendation

Y Hou, J Li, Z He, A Yan, X Chen, J McAuley - ar** a universal model that can efficiently and effectively respond to a wide range of
information access requests-from retrieval to recommendation to question answering---has …

JaColBERTv2. 5: Optimising Multi-Vector Retrievers to Create State-of-the-Art Japanese Retrievers with Constrained Resources

B Clavié - arxiv preprint arxiv:2407.20750, 2024 - arxiv.org
Neural Information Retrieval has advanced rapidly in high-resource languages, but progress
in lower-resource ones such as Japanese has been hindered by data scarcity, among other …

Pre-training with aspect-content text mutual prediction for multi-aspect dense retrieval

X Sun, K Bi, J Guo, X Ma, Y Fan, H Shan… - Proceedings of the …, 2023 - dl.acm.org
Grounded on pre-trained language models (PLMs), dense retrieval has been studied
extensively on plain text. In contrast, there has been little research on retrieving data with …

Pitfalls in link prediction with graph neural networks: Understanding the impact of target-link inclusion & better practices

J Zhu, Y Zhou, VN Ioannidis, S Qian, W Ai… - Proceedings of the 17th …, 2024 - dl.acm.org
While Graph Neural Networks (GNNs) are remarkably successful in a variety of high-impact
applications, we demonstrate that, in link prediction, the common practices of including the …