Papers by Elizaveta Pertseva

1 papers
Fine-tuned LLMs Know More, Hallucinate Less with Few-Shot Sequence-to-Sequence Semantic Parsing over Wikidata (2023.emnlp-main)

Copied to clipboard

Challenge: Large language models can answer many questions correctly, but can also hallucinate and give wrong answers.
Approach: They propose a question-answering benchmark for Wikidata that uses SPARQL to ground large language models.
Outcome: The proposed method outperforms the state-of-the-art for QALD-7 by 3.6% in F1 score.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations