4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.IR2026
EnterpriseRAG-Bench: A RAG Benchmark for Company Internal Knowledge
Yuhong Sun, Joachim Rahmfeld, Chris Weaver +4
Retrieval-Augmented Generation (RAG) has become the standard approach for grounding large language models in information that was not available during training. While existing data…
cs.AI2020★ 4 cited
SeqGenSQL -- A Robust Sequence Generation Model for Structured Query Language
Ning Li, Bethany Keller, Mark Butler +1
We explore using T5 (Raffel et al. (2019)) to directly translate natural language questions into SQL statements. General purpose natural language that interfaces to information sto…
cs.CL2016
Neural Discourse Modeling of Conversations
John M. Pierre, Mark Butler, Jacob Portnoff +1
Deep neural networks have shown recent promise in many language-related tasks such as the modeling of conversations. We extend RNN-based sequence to sequence models to capture the…