3 citations · 5 across the 9 of their papers we have counts for
9 papers
Speaking the Language of Science: Toward a General-Purpose Generative Foundation Model for the Natural Sciences
Mingyang Li, Yurou Liu, Jieping Ye +3
In this report, we present LOGOS (Language Of Generative Objects in Science), a scientific generative language model that unifies heterogeneous tasks across the natural sciences wi…
LLaDA-o: An Effective and Length-Adaptive Omni Diffusion Model
Zebin You, Xiaolu Zhang, Jun Zhou +2
We present \textbf{LLaDA-o}, an effective and length-adaptive omni diffusion model for multimodal understanding and generation. LLaDA-o is built on a Mixture of Diffusion (MoD) fra…
Diff-3DCap: Shape Captioning with Diffusion Models
Zhenyu Shu, Jiawei Wen, Shiyang Li +2
The task of 3D shape captioning occupies a significant place within the domain of computer graphics and has garnered considerable interest in recent years. Traditional approaches t…
Enhancing Reward Models for High-quality Image Generation: Beyond Text-Image Alignment
Ying Ba, Tianyu Zhang, Yalong Bai +4
Contemporary image generation systems have achieved high fidelity and superior aesthetic quality beyond basic text-image alignment. However, existing evaluation frameworks have fai…
Regulatory DNA sequence Design with Reinforcement Learning
Zhao Yang, Bing Su, Chuan Cao +1
Cis-regulatory elements (CREs), such as promoters and enhancers, are relatively short DNA sequences that directly regulate gene expression. The fitness of CREs, measured by their a…
Interpretable Enzyme Function Prediction via Residue-Level Detection
Zhao Yang, Bing Su, Jiahao Chen +1
Predicting multiple functions labeled with Enzyme Commission (EC) numbers from the enzyme sequence is of great significance but remains a challenge due to its sparse multi-label cl…
Uniform Attention Maps: Boosting Image Fidelity in Reconstruction and Editing
Wenyi Mo, Tianyu Zhang, Yalong Bai +2
Text-guided image generation and editing using diffusion models have achieved remarkable advancements. Among these, tuning-free methods have gained attention for their ability to p…
Dynamic Prompt Optimizing for Text-to-Image Generation
Wenyi Mo, Tianyu Zhang, Yalong Bai +3
Text-to-image generative models, specifically those based on diffusion models like Imagen and Stable Diffusion, have made substantial advancements. Recently, there has been a surge…
Supporting Vision-Language Model Inference with Confounder-pruning Knowledge Prompt
Jiangmeng Li, Wenyi Mo, Wenwen Qiang +4
Vision-language models are pre-trained by aligning image-text pairs in a common space to deal with open-set visual concepts. To boost the transferability of the pre-trained models,…