74 citations · 469 across the 219 of their papers we have counts for
23 papers · 1 filter
Merging Vision Transformers from Different Tasks and Domains
Peng Ye, Chenyu Huang, Mingzhu Shen +4
This work targets to merge various Vision Transformers (ViTs) trained on different tasks (i.e., datasets with different object categories) or domains (i.e., datasets with the same…
Partial Fine-Tuning: A Successor to Full Fine-Tuning for Vision Transformers
Peng Ye, Yongqi Huang, Chongjun Tu +4
Fine-tuning pre-trained foundation models has gained significant popularity in various research fields. Existing methods for fine-tuning can be roughly divided into two categories,…
Efficient Architecture Search via Bi-level Data Pruning
Chongjun Tu, Peng Ye, Weihao Lin +5
Improving the efficiency of Neural Architecture Search (NAS) is a challenging but significant task that has received much attention. Previous works mainly adopted the Differentiabl…
ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing
Zhi Jin, Sheng Xu, Xiang Zhang +6
De novo peptide sequencing from mass spectrometry (MS) data is a critical task in proteomics research. Traditional de novo algorithms have encountered a bottleneck in accuracy due…
ResoNet: Robust and Explainable ENSO Forecasts with Hybrid Convolution and Transformer Networks
Pumeng Lyu, Tao Tang, Fenghua Ling +4
Recent studies have shown that deep learning (DL) models can skillfully predict the El Niño-Southern Oscillation (ENSO) forecasts over 1.5 years ahead. However, concerns regarding…
A Perspective of Q-value Estimation on Offline-to-Online Reinforcement Learning
Yinmin Zhang, Jie Liu, Chuming Li +4
Offline-to-online Reinforcement Learning (O2O RL) aims to improve the performance of offline pretrained policy using only a few online samples. Built on offline RL algorithms, most…
Towards an end-to-end artificial intelligence driven global weather forecasting system
Kun Chen, Lei Bai, Fenghua Ling +9
The weather forecasting system is important for science and society, and significant achievements have been made in applying artificial intelligence (AI) to medium-range weather fo…
FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
Yi Xiao, Lei Bai, Wei Xue +3
Weather forecasting is a crucial yet highly challenging task. With the maturity of Artificial Intelligence (AI), the emergence of data-driven weather forecasting models has opened…
Point Transformer V3: Simpler, Faster, Stronger
Xiaoyang Wu, Li Jiang, Peng-Shuai Wang +6
This paper is not motivated to seek innovation within the attention mechanism. Instead, it focuses on overcoming the existing trade-offs between accuracy and efficiency within the…
UniDream: Unifying Diffusion Priors for Relightable Text-to-3D Generation
Zexiang Liu, Yangguang Li, Youtian Lin +7
Recent advancements in text-to-3D generation technology have significantly advanced the conversion of textual descriptions into imaginative well-geometrical and finely textured 3D…
Point Cloud Pre-training with Diffusion Models
Xiao Zheng, Xiaoshui Huang, Guofeng Mei +5
Pre-training a model and then fine-tuning it on downstream tasks has demonstrated significant success in the 2D image and NLP domains. However, due to the unordered and non-uniform…
GPT4Vis: What Can GPT-4 Do for Zero-shot Visual Recognition?
Wenhao Wu, Huanjin Yao, Mengxi Zhang +3
This paper does not present a novel method. Instead, it delves into an essential, yet must-know baseline in light of the latest advancements in Generative Artificial Intelligence (…
Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE
Zeren Chen, Ziqin Wang, Zhen Wang +7
Recent studies have demonstrated Large Language Models (LLMs) can extend their zero-shot generalization capabilities to multimodal learning through instruction tuning. As more moda…
Towards Fair and Comprehensive Comparisons for Image-Based 3D Object Detection
Xinzhu Ma, Yongtao Wang, Yinmin Zhang +5
In this work, we build a modular-designed codebase, formulate strong training recipes, design an error diagnosis toolbox, and discuss current methods for image-based 3D object dete…
MaskMA: Towards Zero-Shot Multi-Agent Decision Making with Mask-Based Collaborative Learning
Jie Liu, Yinmin Zhang, Chuming Li +4
Building a single generalist agent with strong zero-shot capability has recently sparked significant advancements. However, extending this capability to multi-agent decision making…
PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm
Haoyi Zhu, Honghui Yang, Xiaoyang Wu +8
In contrast to numerous NLP and 2D vision foundational models, learning a 3D foundational model poses considerably greater challenges. This is primarily due to the inherent data va…
UniPAD: A Universal Pre-training Paradigm for Autonomous Driving
Honghui Yang, Sha Zhang, Di Huang +9
In the context of autonomous driving, the significance of effective feature learning is widely acknowledged. While conventional 3D self-supervised pre-training methods have shown w…
Toward Understanding BERT-Like Pre-Training for DNA Foundation Models
Chaoqi Liang, Lifeng Qiao, Peng Ye +9
With the success of large-scale pre-training in language tasks, there is an increasing trend of applying it to the domain of life sciences. In particular, pre-training methods base…
Beyond One-Preference-Fits-All Alignment: Multi-Objective Direct Preference Optimization
Zhanhui Zhou, Jie Liu, Jing Shao +4
A single language model, even when aligned with labelers through reinforcement learning from human feedback (RLHF), may not suit all human preferences. Recent approaches therefore…
Understanding Masked Autoencoders From a Local Contrastive Perspective
Xiaoyu Yue, Lei Bai, Meng Wei +4
Masked AutoEncoder (MAE) has revolutionized the field of self-supervised learning with its simple yet effective masking and reconstruction strategies. However, despite achieving st…
RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models
Zekun Moore Wang, Zhongyuan Peng, Haoran Que +14
The advent of Large Language Models (LLMs) has paved the way for complex tasks such as role-playing, which enhances user interactions by enabling models to imitate various characte…
Geometry-enhanced Pre-training on Interatomic Potentials
Taoyong Cui, Chenyu Tang, Mao Su +6
Machine learning interatomic potentials (MLIPs) enables molecular dynamics (MD) simulations with ab initio accuracy and has been applied to various fields of physical science. Howe…
Pro-PRIME: A general Temperature-Guided Language model to engineer enhanced Stability and Activity in Proteins
Fan Jiang, Mingchen Li, Jiajun Dong +23
Designing protein mutants of both high stability and activity is a critical yet challenging task in protein engineering. Here, we introduce PRIME, a deep learning model, which can…