3 citations · 4 across the 14 of their papers we have counts for
Showing cs.CLShow all
2 papers · 1 filter
cs.CL2026
Why Fine-Tuning Encourages Hallucinations and How to Fix It
Guy Kaplan, Zorik Gekhman, Zhen Zhu +5
Large language models are prone to hallucinating factually incorrect statements. A key source of these errors is exposure to new factual information through supervised fine-tuning…
cs.CL2023★ 1 cited
WebWISE: Web Interface Control and Sequential Exploration with Large Language Models
Heyi Tao, Sethuraman T, Michal Shlapentokh-Rothman +1
The paper investigates using a Large Language Model (LLM) to automatically perform web software tasks using click, scroll, and text input operations. Previous approaches, such as r…