Shulin Cao

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 …

Reasoning over Hierarchical Question Decomposition Tree for Explainable Question Answering

2023 · arXiv (Cornell University)

Explainable question answering (XQA) aims to answer a given question and provide an explanation why the answer is selected. Existing XQA methods focus on reasoning on a single knowledge source, e.g., structured knowledge bases, unstructured …

LongCite: Enabling LLMs to Generate Fine-grained Citations in Long-context QA

2024 · arXiv (Cornell University)

Though current long-context large language models (LLMs) have demonstrated impressive capacities in answering user questions based on extensive text, the lack of citations in their responses makes user verification difficult, leading to concerns about their …