Conversation Summarization
13 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Conversation Summarization
| Trend | Dataset | Best Model | Paper | Code | Compare |
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SAMSum
Most implemented papers
The Cross-lingual Conversation Summarization Challenge
We propose the shared task of cross-lingual conversation summarization, \emph{ConvSumX Challenge}, opening new avenues for researchers to investigate solutions that integrate conversation summarization and machine translation.
Summarizing Medical Conversations via Identifying Important Utterances
cuhksz-nlp/het-mc
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COLING 2020
For the particular dataset used in this study, we show that high-quality summaries can be generated by extracting two types of utterances, namely, problem statements and treatment recommendations.
Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs
GT-SALT/Structure-Aware-BART
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NAACL 2021
Abstractive conversation summarization has received much attention recently.
ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining
Yale-LILY/ConvoSumm
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ACL 2021
While online conversations can cover a vast amount of information in many different formats, abstractive text summarization has primarily focused on modeling solely news articles.
Adding more data does not always help: A study in medical conversation summarization with PEGASUS
Summarized conversations are used to facilitate patient hand-offs between physicians, and as part of providing care in the future.
DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents
Large language models (LLMs) have emerged as valuable tools for many natural language understanding tasks.
IUTEAM1 at MEDIQA-Chat 2023: Is simple fine tuning effective for multilayer summarization of clinical conversations?
dhananjay-srivastava/mediqa-chat-2023-iuteam1
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Clinical conversation summarization has become an important application of Natural language Processing.
Revisiting Cross-Lingual Summarization: A Corpus-based Study and A New Benchmark with Improved Annotation
cylnlp/convsumx
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Additionally, based on the same intuition, we propose a 2-Step method, which takes both conversation and summary as input to simulate human annotation process.
Experience and Evidence are the eyes of an excellent summarizer! Towards Knowledge Infused Multi-modal Clinical Conversation Summarization
We propose a knowledge-infused, multi-modal, multi-tasking medical domain identification and clinical conversation summary generation (MM-CliConSummation) framework.
Real-time Speech Summarization for Medical Conversations
Secondly, we present VietMed-Sum which, to our knowledge, is the first speech summarization dataset for medical conversations.
