3 papers
cs.CL2025
Evaluating the Evaluation of Diversity in Commonsense Generation
Tianhui Zhang, Bei Peng, Danushka Bollegala
In commonsense generation, given a set of input concepts, a model must generate a response that is not only commonsense bearing, but also capturing multiple diverse viewpoints. Num…
cs.CV2024
Enhancing Texture Generation with High-Fidelity Using Advanced Texture Priors
Kuo Xu, Maoyu Wang, Muyu Wang +3
The recent advancements in 2D generation technology have sparked a widespread discussion on using 2D priors for 3D shape and texture content generation. However, these methods ofte…
cs.CL2023
Learning to Predict Concept Ordering for Common Sense Generation
Tianhui Zhang, Danushka Bollegala, Bei Peng
Prior work has shown that the ordering in which concepts are shown to a commonsense generator plays an important role, affecting the quality of the generated sentence. However, it…