3 papers
cs.CL2025
Unmasking Deceptive Visuals: Benchmarking Multimodal Large Language Models on Misleading Chart Question Answering
Zixin Chen, Sicheng Song, Kashun Shum +4
Misleading visualizations, which manipulate chart representations to support specific claims, can distort perception and lead to incorrect conclusions. Despite decades of research,…
cs.CL2025
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Kashun Shum, Yuzhen Huang, Hongjian Zou +5
Language model pretraining involves training on extensive corpora, where data quality plays a pivotal role. In this work, we aim to directly estimate the contribution of data durin…
cs.CL2024
FIRST: Teach A Reliable Large Language Model Through Efficient Trustworthy Distillation
KaShun Shum, Minrui Xu, Jianshu Zhang +5
Large language models (LLMs) have become increasingly prevalent in our daily lives, leading to an expectation for LLMs to be trustworthy -- - both accurate and well-calibrated (the…