This repository contains the SciAux dataset, introduced in the paper Thinking in a Crowd: How Auxiliary Information Shapes LLM Reasoning.
SciAux is a new dataset derived from ScienceQA, designed to systematically test the robustness of Large Language Models (LLMs) against various types of auxiliary information (helpful, irrelevant, or misleading). The dataset aims to investigate the causal impact of such information on the reasoning process of LLMs with explicit step-by-step thinking… See the full description on the dataset page:
https://huggingface.co/datasets/billhdzhao/SciAux.
