2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.IR2024
Best Practices for Distilling Large Language Models into BERT for Web Search Ranking
Dezhi Ye, Junwei Hu, Jiabin Fan +4
Recent studies have highlighted the significant potential of Large Language Models (LLMs) as zero-shot relevance rankers. These methods predominantly utilize prompt learning to ass…
cs.CL2022★ 2 cited
Type-enriched Hierarchical Contrastive Strategy for Fine-Grained Entity Typing
Xinyu Zuo, Haijin Liang, Ning Jing +3
Fine-grained entity typing (FET) aims to deduce specific semantic types of the entity mentions in text. Modern methods for FET mainly focus on learning what a certain type looks li…
cs.CL2022
ChiQA: A Large Scale Image-based Real-World Question Answering Dataset for Multi-Modal Understanding
Bingning Wang, Feiyang Lv, Ting Yao +4
Visual question answering is an important task in both natural language and vision understanding. However, in most of the public visual question answering datasets such as VQA, CLE…