3 papers
cs.HC2026
Relying on LLMs: Student Practices and Instructor Norms are Changing in Computer Science Education
Xinrui Lin, Heyan Huang, Shumin Shi +1
Prior research has raised concerns about students' over-reliance on large language models (LLMs) in higher education. This paper examines how Computer Science students and instruct…
cs.CL2025
Do Retrieval Augmented Language Models Know When They Don't Know?
Youchao Zhou, Heyan Huang, Yicheng Liu +5
Existing large language models (LLMs) occasionally generate plausible yet factually incorrect responses, known as hallucinations. Two main approaches have been proposed to mitigate…
cs.CL2022
U3E: Unsupervised and Erasure-based Evidence Extraction for Machine Reading Comprehension
Suzhe He, Shumin Shi, Chenghao Wu
More tasks in Machine Reading Comprehension(MRC) require, in addition to answer prediction, the extraction of evidence sentences that support the answer. However, the annotation of…