A comprehensive survey on process-oriented automatic text summarization with exploration of llm-based methods

H Jin, Y Zhang, D Meng, J Wang, J Tan - arXiv preprint arXiv:2403.02901, 2024 - arxiv.org
Automatic Text Summarization (ATS), utilizing Natural Language Processing (NLP)
algorithms, aims to create concise and accurate summaries, thereby significantly reducing …

Taxonomy of abstractive dialogue summarization: scenarios, approaches, and future directions

Q Jia, Y Liu, S Ren, KQ Zhu - ACM Computing Surveys, 2023 - dl.acm.org
Abstractive dialogue summarization generates a concise and fluent summary covering the
salient information in a dialogue among two or more interlocutors. It has attracted significant …

Augmenting operations research with auto-formulation of optimization models from problem descriptions

R Ramamonjison, H Li, TT Yu, S He, V Rengan… - arXiv preprint arXiv …, 2022 - arxiv.org
We describe an augmented intelligence system for simplifying and enhancing the modeling
experience for operations research. Using this system, the user receives a suggested …

What's Wrong? Refining Meeting Summaries with LLM Feedback

F Kirstein, T Ruas, B Gipp - arXiv preprint arXiv:2407.11919, 2024 - arxiv.org
Meeting summarization has become a critical task since digital encounters have become a
common practice. Large language models (LLMs) show great potential in summarization …

Gpt-calls: Enhancing call segmentation and tagging by generating synthetic conversations via large language models

I Malkiel, U Alon, Y Yehuda, S Keren, O Barkan… - arXiv preprint arXiv …, 2023 - arxiv.org
Transcriptions of phone calls are of significant value across diverse fields, such as sales,
customer service, healthcare, and law enforcement. Nevertheless, the analysis of these …

Team zoom@ automin 2023: Utilizing topic segmentation and llm data augmentation for long-form meeting summarization

F Schneider, M Turchi - … of the 16th International Natural Language …, 2023 - aclanthology.org
This paper describes Zoom's submission to the Second Shared Task on Automatic Minuting
at INLG 2023. We participated in Task A: generating abstractive summaries of meetings. Our …

Utterance-Aware Adaptive Data Labeling and Summarization: Exploiting Large Language Models for Unbiased Dialog Annotation

N Glazkov, I Makarov - IEEE Access, 2024 - ieeexplore.ieee.org
The field of dialogue summarization has advanced significantly with large language models
(LLMs), but their effectiveness can be limited by the size and diversity of training data, as …

HyFit: Hybrid Fine-Tuning With Diverse Sampling for Abstractive Summarization

S Zhao, Y Cheng, Y Zhang, J Chen… - … Transactions on Big …, 2024 - ieeexplore.ieee.org
Abstractive summarization has made significant progress in recent years, which aims to
generate a concise and coherent summary that contains the most important facts from the …

A Dialogues Summarization Algorithm Based on Multi-task Learning

H Chen, C Li, J Liang, L Tian - Neural Processing Letters, 2024 - Springer
With the continuous advancement of social information, the number of texts in the form of
dialogue between individuals has exponentially increased. However, it is very challenging …

SEGLLM: Topic-Oriented Call Segmentation Via LLM-Based Conversation Synthesis

I Malkiel, U Alon, Y Yehuda, S Keren… - ICASSP 2024-2024 …, 2024 - ieeexplore.ieee.org
Transcriptions of phone calls are of significant value across diverse fields, such as sales,
customer service, healthcare, and law enforcement. Nevertheless, the analysis of these …