ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2008.02460
  4. Cited By
DeText: A Deep Text Ranking Framework with BERT

DeText: A Deep Text Ranking Framework with BERT

International Conference on Information and Knowledge Management (CIKM), 2020
6 August 2020
Weiwei Guo
Xiaowei Liu
Sida Wang
Huiji Gao
A. Sankar
Zimeng Yang
Qi Guo
Liang Zhang
Bo Long
Bee-Chung Chen
D. Agarwal
ArXiv (abs)PDFHTML

Papers citing "DeText: A Deep Text Ranking Framework with BERT"

11 / 11 papers shown
OKRA: an Explainable, Heterogeneous, Multi-Stakeholder Job Recommender System
OKRA: an Explainable, Heterogeneous, Multi-Stakeholder Job Recommender SystemEuropean Conference on Information Retrieval (ECIR), 2025
Roan Schellingerhout
Francesco Barile
N. Tintarev
CML
321
1
0
17 Mar 2025
Sentiment Analysis of Movie Reviews Using BERT
Sentiment Analysis of Movie Reviews Using BERT
Gibson Nkhata
Usman Anjum
J. Zhan
289
10
0
26 Feb 2025
AI-Driven Cyber Threat Intelligence Automation
AI-Driven Cyber Threat Intelligence Automation
Shrit Shah
Fatemeh Khoda Parast
90
9
0
26 Oct 2024
Beyond Accuracy: An Empirical Study on Unit Testing in Open-source Deep
  Learning Projects
Beyond Accuracy: An Empirical Study on Unit Testing in Open-source Deep Learning Projects
Han Wang
Sijia Yu
Chunyang Chen
Burak Turhan
Xiaodong Zhu
ELMMLAU
242
5
0
26 Feb 2024
BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model
  with Non-textual Features for CTR Prediction
BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR PredictionKnowledge Discovery and Data Mining (KDD), 2023
Dong Wang
Kave Salamatian
Yunqing Xia
Weiwei Deng
Qi Zhang
198
22
0
17 Aug 2023
Improving Domain-Specific Retrieval by NLI Fine-Tuning
Improving Domain-Specific Retrieval by NLI Fine-TuningConference on Computer Science and Information Systems (FedCSIS), 2023
Roman Dusek
A. Wawer
Christopher Galias
Lidia Wojciechowska
253
2
0
06 Aug 2023
A Comprehensive Survey on Trustworthy Recommender Systems
A Comprehensive Survey on Trustworthy Recommender Systems
Wenqi Fan
Xiangyu Zhao
Xiao Chen
Jingran Su
Jingtong Gao
...
Qidong Liu
Yiqi Wang
Hanfeng Xu
Lei Chen
Qing Li
FaML
298
68
0
21 Sep 2022
ItemSage: Learning Product Embeddings for Shopping Recommendations at
  Pinterest
ItemSage: Learning Product Embeddings for Shopping Recommendations at PinterestKnowledge Discovery and Data Mining (KDD), 2022
Paul Baltescu
Haoyu Chen
Nikil Pancha
Andrew Zhai
J. Leskovec
Charles R. Rosenberg
DML
248
48
0
24 May 2022
Modeling Relevance Ranking under the Pre-training and Fine-tuning
  Paradigm
Modeling Relevance Ranking under the Pre-training and Fine-tuning Paradigm
Lin Bo
Liang Pang
Gang Wang
Jun Xu
Xiuqiang He
Jirong Wen
156
5
0
12 Aug 2021
MathBERT: A Pre-trained Language Model for General NLP Tasks in
  Mathematics Education
MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education
J. Shen
Michiharu Yamashita
Ethan Prihar
Neil T. Heffernan
Xintao Wu
Ben Graff
Dongwon Lee
397
85
0
02 Jun 2021
Ranking Creative Language Characteristics in Small Data Scenarios
Ranking Creative Language Characteristics in Small Data ScenariosInternational Conference on Innovative Computing and Cloud Computing (ICCC), 2020
Julia Siekiera
M. Koppel
Edwin Simpson
Kevin Stowe
Iryna Gurevych
Stefan Kramer
BDL
130
4
0
23 Oct 2020
1
Page 1 of 1