406 citations · 2.4k across the 39 of their papers we have counts for
5 papers · 1 filter
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…
DIONYSUS: A Pre-trained Model for Low-Resource Dialogue Summarization
Yu Li, Baolin Peng, Pengcheng He +3
Dialogue summarization has recently garnered significant attention due to its wide range of applications. However, existing methods for summarizing dialogues have limitations becau…
Enhancing Task Bot Engagement with Synthesized Open-Domain Dialog
Miaoran Li, Baolin Peng, Michel Galley +2
Many efforts have been made to construct dialog systems for different types of conversations, such as task-oriented dialog (TOD) and open-domain dialog (ODD). To better mimic human…
GODEL: Large-Scale Pre-Training for Goal-Directed Dialog
Baolin Peng, Michel Galley, Pengcheng He +6
We introduce GODEL (Grounded Open Dialogue Language Model), a large pre-trained language model for dialog. In contrast with earlier models such as DialoGPT, GODEL leverages a new p…
Probing Factually Grounded Content Transfer with Factual Ablation
Peter West, Chris Quirk, Michel Galley +1
Despite recent success, large neural models often generate factually incorrect text. Compounding this is the lack of a standard automatic evaluation for factuality--it cannot be me…