Efficient Adaptation of Pretrained Transformers for Abstractive
Summarization

Efficient Adaptation of Pretrained Transformers for Abstractive Summarization

1 June 2019

Antoine Bosselut

Asli Celikyilmaz

Yejin Choi

Papers citing "Efficient Adaptation of Pretrained Transformers for Abstractive Summarization"

7 / 7 papers shown

Title
Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report Paul Kassianik Baturay Saglam Alexander Chen Blaine Nelson Anu Vellore ... Hyrum Anderson Kojin Oshiba Omar Santos Yaron Singer Amin Karbasi PILM 66 1 0 28 Apr 2025
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models Yu He Boheng Li L. Liu Zhongjie Ba Wei Dong Yiming Li Zhan Qin Kui Ren Chong Chen MIALM 74 0 0 26 Feb 2025
BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Models Haoxiang Luo Jian Luo Athanasios V. Vasilakos 34 9 0 10 Oct 2023
Nutribullets Hybrid: Multi-document Health Summarization Darsh J. Shah L. Yu Tao Lei Regina Barzilay 41 3 0 08 Apr 2021
Summary Level Training of Sentence Rewriting for Abstractive Summarization Sanghwan Bae Taeuk Kim Jihoon Kim Sang-goo Lee 38 68 0 19 Sep 2019
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 299 6,996 0 20 Apr 2018
SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents Ramesh Nallapati Feifei Zhai Bowen Zhou 207 1,255 0 14 Nov 2016