1 citations · 1 across the 3 of their papers we have counts for
3 papers
A Causality-aware Paradigm for Evaluating Creativity of Multimodal Large Language Models
Zhongzhan Huang, Shanshan Zhong, Pan Zhou +3
Recently, numerous benchmarks have been developed to evaluate the logical reasoning abilities of large language models (LLMs). However, assessing the equally important creative cap…
MoExtend: Tuning New Experts for Modality and Task Extension
Shanshan Zhong, Shanghua Gao, Zhongzhan Huang +3
Large language models (LLMs) excel in various tasks but are primarily trained on text data, limiting their application scope. Expanding LLM capabilities to include vision-language…
Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation
Shanshan Zhong, Zhongzhan Huang, Shanghua Gao +4
Chain-of-Thought (CoT) guides large language models (LLMs) to reason step-by-step, and can motivate their logical reasoning ability. While effective for logical tasks, CoT is not c…