Pith. sign in

REVIEW 1 cited by

Hierarchical Text Generation using an Outline

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1810.08802 v1 pith:V62WCC36 submitted 2018-10-20 cs.CL cs.LGstat.ML

classification cs.CLcs.LGstat.ML
keywords textgenerationoutlinehumanlanguagebecomesevaluationfind
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Many challenges in natural language processing require generating text, including language translation, dialogue generation, and speech recognition. For all of these problems, text generation becomes more difficult as the text becomes longer. Current language models often struggle to keep track of coherence for long pieces of text. Here, we attempt to have the model construct and use an outline of the text it generates to keep it focused. We find that the usage of an outline improves perplexity. We do not find that using the outline improves human evaluation over a simpler baseline, revealing a discrepancy in perplexity and human perception. Similarly, hierarchical generation is not found to improve human evaluation scores.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Progressive Document-level Text Simplification via Large Language Models

    cs.CL 2025-01 conditional novelty 6.0 of 10

    A three-stage hierarchical LLM pipeline for document simplification outperforms direct ChatGPT prompts and earlier methods on Wiki-auto and Newsela, with caveats about self-evaluation.

Pith tools