8 citations · 31 across the 12 of their papers we have counts for
3 papers · 1 filter
Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitation
David Eric Austin, Anton Korikov, Armin Toroghi +1
Designing preference elicitation (PE) methodologies that can quickly ascertain a user's top item preferences in a cold-start setting is a key challenge for building effective and p…
CR-LT-KGQA: A Knowledge Graph Question Answering Dataset Requiring Commonsense Reasoning and Long-Tail Knowledge
Willis Guo, Armin Toroghi, Scott Sanner
Knowledge graph question answering (KGQA) is a well-established field that seeks to provide factual answers to natural language (NL) questions by leveraging knowledge graphs (KGs).…
Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answering
Armin Toroghi, Willis Guo, Mohammad Mahdi Abdollah Pour +1
Knowledge Graph Question Answering (KGQA) methods seek to answer Natural Language questions using the relational information stored in Knowledge Graphs (KGs). With the recent advan…