2 papers
cs.CV2026
Timage: A Generative Text-in-Image Paradigm for Fine-Tuning Vision-Language Models
Yifeng Wu, Huimin Huang, Ruiluo Wu +5
Multimodal Large Language Models (MLLMs) often lose track of the right image regions during fine-grained spatial reasoning, because a textual query rarely carries any explicit geom…
cs.CL2020
TaylorGAN: Neighbor-Augmented Policy Update for Sample-Efficient Natural Language Generation
Chun-Hsing Lin, Siang-Ruei Wu, Hung-Yi Lee +1
Score function-based natural language generation (NLG) approaches such as REINFORCE, in general, suffer from low sample efficiency and training instability problems. This is mainly…