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. 2105.00944
  4. Cited By
Explaining Outcomes of Multi-Party Dialogues using Causal Learning

Explaining Outcomes of Multi-Party Dialogues using Causal Learning

3 May 2021
Priyankar Sinha
Pabitra Mitra
Antonio Anastasio Bruto da Costa
Nikolaos Kekatos
ArXivPDFHTML

Papers citing "Explaining Outcomes of Multi-Party Dialogues using Causal Learning"

3 / 3 papers shown
Title
A Multi-Modal Explainability Approach for Human-Aware Robots in Multi-Party Conversation
A Multi-Modal Explainability Approach for Human-Aware Robots in Multi-Party Conversation
Iveta Becková
Stefan Pócos
Giulia Belgiovine
Marco Matarese
A. Sciutti
Carlo Mazzola
Carlo Mazzola
80
0
0
20 May 2024
A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues
A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues
Zhouxing Shi
Minlie Huang
58
100
0
01 Dec 2018
Empath: Understanding Topic Signals in Large-Scale Text
Empath: Understanding Topic Signals in Large-Scale Text
Ethan Fast
Binbin Chen
Michael S. Bernstein
VLM
55
387
0
22 Feb 2016
1