mlsanityData to 7 Oct 2026

Multi-LLM Text Summarization

arXiv 2412.15487 ↗First posted 20 Dec 2024cs.CLcited by 5

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Abstract (arXiv)

In this work, we propose a Multi-LLM summarization framework, and investigate two different multi-LLM strategies including centralized and decentralized. Our multi-LLM summarization framework has two fundamentally important steps at each round of conversation: generation and evaluation. These steps are different depending on whether our multi-LLM decentralized summarization is used or centralized. In both our multi-LLM decentralized and centralized strategies, we have k different LLMs that generate diverse summaries of the text. However, during evaluation, our multi-LLM centralized summarization approach leverages a single LLM to evaluate the summaries and select the best one whereas k LLMs are used for decentralized multi-LLM summarization. Overall, we find that our multi-LLM summarization approaches significantly outperform the baselines that leverage only a single LLM by up to 3x. These results indicate the effectiveness of multi-LLM approaches for summarization.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 31 of its 45 references that are in the map. First posted on arXiv 20 Dec 2024.

Builds on

31 of 45 references.

References · 31

  1. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  2. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  3. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
  4. 2020Longformer: The Long-Document Transformercited by 3,362
  5. 2019Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contextcited by 1,830
  6. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,739
  7. 2020Big Bird: Transformers for Longer Sequencescited by 1,673
  8. 2018Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationcited by 1,308
  9. 2017Get To The Point: Summarization with Pointer-Generator Networkscited by 1,281
  10. 2019PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarizationcited by 1,100
  11. 2015Teaching Machines to Read and Comprehendcited by 1,039
  12. 2016Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyondcited by 809
19 more
  1. 2023Large Language Modelscited by 774
  2. 2019Text Summarization with Pretrained Encoderscited by 553
  3. 2018A Discourse-Aware Attention Model for Abstractive Summarization of Long Documentscited by 477
  4. 2023Benchmarking Large Language Models for News Summarizationcited by 444
  5. 2015A Neural Attention Model for Abstractive Sentence Summarizationcited by 394
  6. 2021Efficient Attentions for Long Document Summarizationcited by 342
  7. 2023ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMscited by 297
  8. 2021LongT5: Efficient Text-To-Text Transformer for Long Sequencescited by 232
  9. 2022BRIO: Bringing Order to Abstractive Summarizationcited by 161
  10. 2019Adaptive Attention Span in Transformerscited by 148
  11. 2023BooookScore: A systematic exploration of book-length summarization in the era of LLMscited by 137
  12. 2019BillSum: A Corpus for Automatic Summarization of US Legislationcited by 117
  13. 2024Improving Multi-Agent Debate with Sparse Communication Topologycited by 103
  14. 2019Extractive Summarization of Long Documents by Combining Global and Local Contextcited by 59
  15. 2023From Sparse to Dense: GPT-4 Summarization with Chain of Density Promptingcited by 52
  16. 2022Long Document Summarization with Top-down and Bottom-up Inferencecited by 42
  17. 2023Text Summarization Using Large Language Models: A Comparative Study of MPT-7b-instruct, Falcon-7b-instruct, and OpenAI Chat-GPT Modelscited by 35
  18. 2023Incorporating Distributions of Discourse Structure for Long Document Abstractive Summarizationcited by 17
  19. 2023HiPool: Modeling Long Documents Using Graph Neural Networkscited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 1.

5 papers.

  1. 2025Jailbreak-AudioBench: In-Depth Evaluation and Analysis of Jailbreak Threats for Large Audio Language Modelscited by 17
  2. 2025Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent Systemscited by 17
  3. 2026Can Large Language Models Self-Correct in Medical Question Answering? An Exploratory Studycited by 2
  4. 2025Learning to Summarize by Learning to Quiz: Adversarial Agentic Collaboration for Long Document Summarizationcited by 1
  5. 2025LLM-Powered Proactive Data Systemscited by 0