93 citations · 195 across the 16 of their papers we have counts for
7 papers · 1 filter
InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery
He Cao, Zijing Liu, Xingyu Lu +2
The rapid evolution of artificial intelligence in drug discovery encounters challenges with generalization and extensive training, yet Large Language Models (LLMs) offer promise in…
TOSS:High-quality Text-guided Novel View Synthesis from a Single Image
Yukai Shi, Jianan Wang, He Cao +7
In this paper, we present TOSS, which introduces text to the task of novel view synthesis (NVS) from just a single RGB image. While Zero-1-to-3 has demonstrated impressive zero-sho…
ChatCounselor: A Large Language Models for Mental Health Support
June M. Liu, Donghao Li, He Cao +3
This paper presents ChatCounselor, a large language model (LLM) solution designed to provide mental health support. Unlike generic chatbots, ChatCounselor is distinguished by its f…
Leveraging Side Information for Ligand Conformation Generation using Diffusion-Based Approaches
Jiamin Wu, He Cao, Yuan Yao
Ligand molecule conformation generation is a critical challenge in drug discovery. Deep learning models have been developed to tackle this problem, particularly through the use of…
detrex: Benchmarking Detection Transformers
Tianhe Ren, Shilong Liu, Feng Li +13
The DEtection TRansformer (DETR) algorithm has received considerable attention in the research community and is gradually emerging as a mainstream approach for object detection and…
DreamWaltz: Make a Scene with Complex 3D Animatable Avatars
Yukun Huang, Jianan Wang, Ailing Zeng +5
We present DreamWaltz, a novel framework for generating and animating complex 3D avatars given text guidance and parametric human body prior. While recent methods have shown encour…
Inducing Neural Collapse in Deep Long-tailed Learning
Xuantong Liu, Jianfeng Zhang, Tianyang Hu +3
Although deep neural networks achieve tremendous success on various classification tasks, the generalization ability drops sheer when training datasets exhibit long-tailed distribu…