Meetalk: Retrieval-Augmented and Adaptively Personalized Meeting Summarization with Knowledge Learning from User Corrections

Authors

Yue Deng (ORCID: https://orcid.org/0000-0002-8508-1588)
Changyang He (ORCID: https://orcid.org/0000-0001-6648-4456)
Zheng Chen (ORCID: https://orcid.org/0000-0002-9654-0997)
Bo Li (ORCID: https://orcid.org/0000-0003-4883-7267)
Jiang Futian

Publication Details

Published: 2025-01-01
DOI: https://doi.org/10.18653/v1/2025.knowllm-1.9
Primary Topic: Recommender Systems and Techniques
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Meetalk: Retrieval-Augmented and Adaptively Personalized Meeting Summarization with Knowledge Learning from User Corrections

Yue Deng, Changyang He, Zheng Chen, Bo Li et al.

Jan 1, 2025

Recommender Systems and Techniques

article

Meetalk: Retrieval-Augmented and Adaptively Personalized Meeting Summarization with Knowledge Learning from User Corrections

Yue Deng, Changyang He, Zheng Chen, Bo Li, Jiang Futian

January 1, 2025article en

Abstract

No abstract available for this paper.

Quality Education

Openalex Percentile: Top 71%

Recommender Systems and Techniques

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Meetalk: Retrieval-Augmented and Adaptively Personalized Meeting Summarization with Knowledge Learning from User Corrections — Yue Deng, Changyang He, et al. · (2025) | TGRS Research Map | TGRS