Model: lrakotoson/scitldr-catts-xsum-ao
Author: lrakotoson
Library: transformers
Tags: transformers, pytorch, tf, safetensors, bart, text2text-generation, en, dataset:xsum, dataset:scitldr, arxiv:2004.15011, license:apache-2.0, endpoints_compatible, region:us
Card metadata: language: en
datasets: xsum, scitldr
widget: We introduce TLDR generation, a new form of extreme summarization, for scientific papers. TLDR generation involves high source compression and requires expert background knowledge and understanding of complex domain-specific language. To facilitate study on this task, we introduce SciTLDR, a new multi-target dataset of 5.4K TLDRs over 3.2K papers. SciTLDR contains both author-written and expert-derived TLDRs, where the latter are collected using a novel annotation protocol that produces high-quality summaries while minimizing annotation burden. We propose CATTS, a simple yet effective learning strategy for generating TLDRs that exploits titles as an auxiliary training signal. CATTS improves upon strong baselines under both automated metrics and human evaluations.
license: apache-2.0
Likes: 9 | All-time downloads: 9012
Created: 2022-03-02 23:29:05