T5 casts all NLP tasks as text-to-text generation, systematically explores pre-training choices, and reaches strong performance on summarization, QA, classification and other tasks via large-scale training on the Colossal Clean Crawled Corpus.
citation dossier
Long short-term memory-networks for machine reading.arXiv preprint arXiv:1601.06733
5Pith papers citing it
5reference links
cs.CLtop field · 3 papers
ACCEPTtop verdict bucket · 2 papers
why this work matters in Pith
Pith has found this work in 5 reviewed papers. Its strongest current cluster is cs.CL (3 papers). The largest review-status bucket among citing papers is ACCEPT (2 papers). For highly cited works, this page shows a dossier first and a bounded explorer second; it never tries to render every citing paper at once.
representative citing papers
Graph Attention Networks compute learnable attention coefficients over node neighborhoods to produce weighted feature aggregations, achieving state-of-the-art results on citation networks and inductive protein-protein interaction graphs.
MS MARCO is a new large-scale machine reading comprehension dataset built from real Bing search queries, human-generated answers, and web passages, supporting three tasks including answer synthesis and passage ranking.
Pointer sentinel-LSTM mixes context copying with softmax prediction to reach 70.9 perplexity on Penn Treebank using fewer parameters than standard LSTMs.
Pith review generated a malformed one-line summary.
citing papers explorer
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
T5 casts all NLP tasks as text-to-text generation, systematically explores pre-training choices, and reaches strong performance on summarization, QA, classification and other tasks via large-scale training on the Colossal Clean Crawled Corpus.
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Graph Attention Networks
Graph Attention Networks compute learnable attention coefficients over node neighborhoods to produce weighted feature aggregations, achieving state-of-the-art results on citation networks and inductive protein-protein interaction graphs.
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MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
MS MARCO is a new large-scale machine reading comprehension dataset built from real Bing search queries, human-generated answers, and web passages, supporting three tasks including answer synthesis and passage ranking.
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Pointer Sentinel Mixture Models
Pointer sentinel-LSTM mixes context copying with softmax prediction to reach 70.9 perplexity on Penn Treebank using fewer parameters than standard LSTMs.
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Attention Is All You Need
Pith review generated a malformed one-line summary.