5 citations · 12 across the 4 of their papers we have counts for
4 papers
CoLoTa: A Dataset for Entity-based Commonsense Reasoning over Long-Tail Knowledge
Armin Toroghi, Willis Guo, Scott Sanner
The rise of Large Language Models (LLMs) has redefined the AI landscape, particularly due to their ability to encode factual and commonsense knowledge, and their outstanding perfor…
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…