activity
20192023
most citedPARADE: Passage Representation Aggregation for Document Reranking

44 citations · 77 across the 8 of their papers we have counts for

collaborators

8 papers

cs.IR2023★ 1 cited

Defense of Adversarial Ranking Attack in Text Retrieval: Benchmark and Baseline via Detection

Xuanang Chen, Ben He, Le Sun +1

Neural ranking models (NRMs) have undergone significant development and have become integral components of information retrieval (IR) systems. Unfortunately, recent research has un…

cs.IR2023

Understanding Differential Search Index for Text Retrieval

Xiaoyang Chen, Yanjiang Liu, Ben He +2

The Differentiable Search Index (DSI) is a novel information retrieval (IR) framework that utilizes a differentiable function to generate a sorted list of document identifiers in r…

cs.CL2023

DLUE: Benchmarking Document Language Understanding

Ruoxi Xu, Hongyu Lin, Xinyan Guan +3

Understanding documents is central to many real-world tasks but remains a challenging topic. Unfortunately, there is no well-established consensus on how to comprehensively evaluat…

cs.IR2023★ 2 cited

Towards Imperceptible Document Manipulations against Neural Ranking Models

Xuanang Chen, Ben He, Zheng Ye +2

Adversarial attacks have gained traction in order to identify potential vulnerabilities in neural ranking models (NRMs), but current attack methods often introduce grammatical erro…

cs.CV2022★ 2 cited

End-to-End Transformer Based Model for Image Captioning

Yiyu Wang, Jungang Xu, Yingfei Sun

CNN-LSTM based architectures have played an important role in image captioning, but limited by the training efficiency and expression ability, researchers began to explore the CNN-…

cs.IR2020★ 44 cited

PARADE: Passage Representation Aggregation for Document Reranking

Canjia Li, Andrew Yates, Sean MacAvaney +2

Pretrained transformer models, such as BERT and T5, have shown to be highly effective at ad-hoc passage and document ranking. Due to inherent sequence length limits of these models…

cs.CL2019★ 22 cited

A Survey on Neural Machine Reading Comprehension

Boyu Qiu, Xu Chen, Jungang Xu +1

Enabling a machine to read and comprehend the natural language documents so that it can answer some questions remains an elusive challenge. In recent years, the popularity of deep…

cs.CV2019★ 6 cited

Image Captioning based on Deep Learning Methods: A Survey

Yiyu Wang, Jungang Xu, Yingfei Sun +1

Image captioning is a challenging task and attracting more and more attention in the field of Artificial Intelligence, and which can be applied to efficient image retrieval, intell…