4 citations · 9 across the 10 of their papers we have counts for
16 papers
Grounded Keys-to-Text Generation: Towards Factual Open-Ended Generation
Faeze Brahman, Baolin Peng, Michel Galley +4
Large pre-trained language models have recently enabled open-ended generation frameworks (e.g., prompt-to-text NLG) to tackle a variety of tasks going beyond the traditional data-t…
SPE: Symmetrical Prompt Enhancement for Fact Probing
Yiyuan Li, Tong Che, Yezhen Wang +3
Pretrained language models (PLMs) have been shown to accumulate factual knowledge during pretrainingng (Petroni et al., 2019). Recent works probe PLMs for the extent of this knowle…
Towards Inter-character Relationship-driven Story Generation
Anvesh Rao Vijjini, Faeze Brahman, Snigdha Chaturvedi
In this paper, we introduce the task of modeling interpersonal relationships for story generation. For addressing this task, we propose Relationships as Latent Variables for Story…
Revisiting Generative Commonsense Reasoning: A Pre-Ordering Approach
Chao Zhao, Faeze Brahman, Tenghao Huang +1
Pre-trained models (PTMs) have lead to great improvements in natural language generation (NLG). However, it is still unclear how much commonsense knowledge they possess. With the g…
Read Top News First: A Document Reordering Approach for Multi-Document News Summarization
Chao Zhao, Tenghao Huang, Somnath Basu Roy Chowdhury +3
A common method for extractive multi-document news summarization is to re-formulate it as a single-document summarization problem by concatenating all documents as a single meta-do…
Unsupervised Extractive Opinion Summarization Using Sparse Coding
Somnath Basu Roy Chowdhury, Chao Zhao, Snigdha Chaturvedi
Opinion summarization is the task of automatically generating summaries that encapsulate information from multiple user reviews. We present Semantic Autoencoder (SemAE) to perform…