Unveiling the Art of Heading Design: A Harmonious Blend of Summarization, Neology, and Algorithm
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Date
2024-08
Publication Type
Conference Paper
ETH Bibliography
yes
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Abstract
Crafting an appealing heading is crucial for attracting readers and marketing work or products. A popular way is to summarize the main idea with a refined description and a memorable acronym. However, there lacks a systematic study and a formal benchmark including datasets and metrics. Motivated by this absence, we introduce (LOGOGRAM), a novel benchmark comprising 6,653 paper abstracts with corresponding descriptions and acronyms. To measure the quality of heading generation, we propose a set of evaluation metrics from three aspects: summarization, neology, and algorithm. Additionally, we explore three strategies for heading generation (generation ordering, tokenization of acronyms, and framework design) under various prevalent learning paradigms (supervised fine-tuning, in-context learning with Large Language Models (LLMs), and reinforcement learning) on our benchmark. Our experimental results indicate the difficulty in identifying a practice that excels across all summarization, neologistic, and algorithmic aspects.
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Publication status
published
Book title
Findings of the Association for Computational Linguistics: ACL 2024
Journal / series
Volume
Pages / Article No.
6149 - 6174
Publisher
Association for Computational Linguistics
Event
62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024)