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Found 7 papers, 4 papers with code
Event Graph based Sentence Fusion
Sentence fusion is a conditional generation task that merges several related sentences into a coherent one, which can be deemed as a summary sentence.
The Critique of Critique
In this paper, we pioneer the critique of critique, termed MetaCritique, which is a framework to evaluate the critique from two aspects, i. e., factuality as precision score and comprehensiveness as recall score.
Evolving Large Language Model Assistant with Long-Term Conditional Memory
It focuses on preserving the knowledge and experience from the history dialogue between the user and AI assistant, which can be applied to future dialogue for generating a better response.
RefGPT: Dialogue Generation of GPT, by GPT, and for GPT
Therefore, we propose a method called RefGPT to generate enormous truthful and customized dialogues without worrying about factual errors caused by the model hallucination.
Improving Sentence Similarity Estimation for Unsupervised Extractive Summarization
Unsupervised extractive summarization aims to extract salient sentences from a document as the summary without labeled data.
Few-shot Query-Focused Summarization with Prefix-Merging
Drawn inspiration from prefix-tuning, we are allowed to integrate the task knowledge from text summarization and question answering into a properly designed prefix and apply the merged prefix to query-focused summarization.
Fact-level Extractive Summarization with Hierarchical Graph Mask on BERT
We also introduce a hierarchical structure, which incorporates the multi-level of granularities of the textual information into the model.
