27 citations · 98 across the 9 of their papers we have counts for
13 papers
MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text
Wenhu Chen, Hexiang Hu, Xi Chen +2
While language Models store a massive amount of world knowledge implicitly in their parameters, even very large models often fail to encode information about rare entities and even…
Faithful to the Document or to the World? Mitigating Hallucinations via Entity-linked Knowledge in Abstractive Summarization
Yue Dong, John Wieting, Pat Verga
Despite recent advances in abstractive summarization, current summarization systems still suffer from content hallucinations where models generate text that is either irrelevant or…
Multilingual Fact Linking
Keshav Kolluru, Martin Rezk, Pat Verga +2
Knowledge-intensive NLP tasks can benefit from linking natural language text with facts from a Knowledge Graph (KG). Although facts themselves are language-agnostic, the fact label…
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
Haitian Sun, Pat Verga, Bhuwan Dhingra +2
We present the Open Predicate Query Language (OPQL); a method for constructing a virtual KB (VKB) trained entirely from text. Large Knowledge Bases (KBs) are indispensable for a wi…
Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge
Pat Verga, Haitian Sun, Livio Baldini Soares +1
Massive language models are the core of modern NLP modeling and have been shown to encode impressive amounts of commonsense and factual information. However, that knowledge exists…
Simultaneously Linking Entities and Extracting Relations from Biomedical Text Without Mention-level Supervision
Trapit Bansal, Pat Verga, Neha Choudhary +1
Understanding the meaning of text often involves reasoning about entities and their relationships. This requires identifying textual mentions of entities, linking them to a canonic…