SOTAVerified

Summarization

Summarization is the task of producing a shorter version of one or several documents that preserves most of the input's meaning.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–8 of 8 papers

TitleStatusHype
Sparsifying Transformer Models with Trainable Representation PoolingCode1
Abstractive Text Summarization Using Sequence-to-Sequence RNNs and BeyondCode1
Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive PrinciplesCode1
MuLD: The Multitask Long Document BenchmarkCode1
Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization—0
Abstractive Sentence Summarization with Attentive Recurrent Neural Networks—0
Ensure the Correctness of the Summary: Incorporate Entailment Knowledge into Abstractive Sentence Summarization—0
Faithful to the Original: Fact Aware Neural Abstractive Summarization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LongformerBLEU-146.74—Unverified
2T5BLEU-128.85—Unverified