5 papers
Hallucinate Less by Thinking More: Aspect-Based Causal Abstention for Large Language Models
Vy Nguyen, Ziqi Xu, Jeffrey Chan +3
Large Language Models (LLMs) often produce fluent but factually incorrect responses, a phenomenon known as hallucination. Abstention, where the model chooses not to answer and inst…
Identifying Origins of Place Names via Retrieval Augmented Generation
Alexis Horde-Vo, Matt Duckham, Estrid He +1
Who is the "Batman" behind "Batman Street" in Melbourne? Understanding the historical, cultural, and societal narratives behind place names can reveal the rich context that has sha…
Evaluating Position Bias in Large Language Model Recommendations
Ethan Bito, Yongli Ren, Estrid He
Large Language Models (LLMs) are being increasingly explored as general-purpose tools for recommendation tasks, enabling zero-shot and instruction-following capabilities without th…
Agent-Based Detection and Resolution of Incompleteness and Ambiguity in Interactions with Large Language Models
Riya Naik, Ashwin Srinivasan, Swati Agarwal +1
Many of us now treat LLMs as modern-day oracles asking it almost any kind of question. However, consulting an LLM does not have to be a single turn activity. But long multi-turn in…
An Empirical Study of the Role of Incompleteness and Ambiguity in Interactions with Large Language Models
Riya Naik, Ashwin Srinivasan, Estrid He +1
Natural language as a medium for human-computer interaction has long been anticipated, has been undergoing a sea-change with the advent of Large Language Models (LLMs) with startli…