Enhancing Abstractiveness of Summarization Models through Calibrated Distillation

20 October 2023

Papers citing "Enhancing Abstractiveness of Summarization Models through Calibrated Distillation"

9 / 9 papers shown

Title
References Indeed Matter? Reference-Free Preference Optimization for Conversational Query Reformulation Doyoung Kim Youngjun Lee Joeun Kim Jihwan Bang Hwanjun Song Susik Yoon Jae-Gil Lee 29 0 0 10 May 2025
LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning Zhibin Lan Liqiang Niu Fandong Meng Jie Zhou Jinsong Su VLM 69 0 0 04 Mar 2025
Learning to Summarize from LLM-generated Feedback Hwanjun Song Taewon Yun Yuho Lee Jihwan Oh Gihun Lee Jason (Jinglun) Cai Hang Su 73 2 0 28 Jan 2025
FineSurE: Fine-grained Summarization Evaluation using LLMs Hwanjun Song Hang Su Igor Shalyminov Jason (Jinglun) Cai Saab Mansour HILM 28 29 0 01 Jul 2024
Factual Dialogue Summarization via Learning from Large Language Models Rongxin Zhu Jey Han Lau Jianzhong Qi HILM 46 1 0 20 Jun 2024
Data Augmentation Approaches in Natural Language Processing: A Survey Bohan Li Yutai Hou Wanxiang Che 121 270 0 05 Oct 2021
Text Summarization with Pretrained Encoders Yang Liu Mirella Lapata MILM 254 1,431 0 22 Aug 2019
SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents Ramesh Nallapati Feifei Zhai Bowen Zhou 207 1,254 0 14 Nov 2016
Teaching Machines to Read and Comprehend Karl Moritz Hermann Tomás Kociský Edward Grefenstette L. Espeholt W. Kay Mustafa Suleyman Phil Blunsom 170 3,509 0 10 Jun 2015