ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2409.02965
  4. Cited By
Do We Trust What They Say or What They Do? A Multimodal User Embedding
  Provides Personalized Explanations

Do We Trust What They Say or What They Do? A Multimodal User Embedding Provides Personalized Explanations

4 September 2024
Zhicheng Ren
Zhiping Xiao
Yizhou Sun
ArXivPDFHTML

Papers citing "Do We Trust What They Say or What They Do? A Multimodal User Embedding Provides Personalized Explanations"

3 / 3 papers shown
Title
Detecting Political Biases of Named Entities and Hashtags on Twitter
Detecting Political Biases of Named Entities and Hashtags on Twitter
Zhiping Xiao
Jeffrey Zhu
Yining Wang
Pei Zhou
Wen Hong Lam
M. A. Porter
Yizhou Sun
33
18
0
16 Sep 2022
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
313
11,953
0
04 Mar 2022
Semantics of the Black-Box: Can knowledge graphs help make deep learning
  systems more interpretable and explainable?
Semantics of the Black-Box: Can knowledge graphs help make deep learning systems more interpretable and explainable?
Manas Gaur
Keyur Faldu
A. Sheth
34
113
0
16 Oct 2020
1