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SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive
  Summarization
v1v2 (latest)

SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
27 November 2019
Bogdan Gliwa
Iwona Mochol
M. Biesek
A. Wawer
ArXiv (abs)PDFHTMLHuggingFace (1 upvotes)

Papers citing "SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization"

50 / 422 papers shown
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Russian-Language Multimodal Dataset for Automatic Summarization of
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Evaluating Dialect Robustness of Language Models via Conversation
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To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning
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Large Language Models are Inconsistent and Biased Evaluators
Large Language Models are Inconsistent and Biased Evaluators
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Better & Faster Large Language Models via Multi-token Prediction
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In-Context Learning with Long-Context Models: An In-Depth Exploration
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Make Your LLM Fully Utilize the Context
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