Liangming Pan

KQA Pro: A Large-Scale Dataset with Interpretable Programs and Accurate SPARQLs for Complex Question Answering over Knowledge Base

2020 · arXiv (Cornell University)

Complex question answering over knowledge base (Complex KBQA) is challenging because it requires various compositional reasoning capabilities, such as multi-hop inference, attribute comparison, set operation, and etc. Existing benchmarks have some shortcomings that limit the …

Modeling What-to-ask and How-to-ask for Answer-unaware Conversational Question Generation

2023 · arXiv (Cornell University)

Conversational Question Generation (CQG) is a critical task for machines to assist humans in fulfilling their information needs through conversations. The task is generally cast into two different settings: answer-aware and answer-unaware. While the former …

Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models

2024

This paper investigates the capabilities of Large Language Models (LLMs) in the context of understanding their knowledge and uncertainty over questions.Specifically, we focus on addressing known-unknown questions, characterized by high uncertainty due to the absence …

Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen

2020

The curse of knowledge can impede communication between experts and laymen. We propose a new task of expertise style transfer and contribute a manually annotated dataset with the goal of alleviating such cognitive biases. Solving …