38 citations · 54 across the 27 of their papers we have counts for
10 papers · 1 filter
Posterior Flow Matching
Chenrui Ma, Xi Xiao, Lin Zhao +4
Flow matching learns how to transport noise toward data, but its mean prediction does not directly report the endpoint uncertainty remaining at an intermediate state. This paper in…
Less Tokens, Better Forecasts: Sparse Residual Routing for Efficient Weather Prediction
Janet Wang, Yunbei Zhang, Lin Zhao +3
Existing ViT-based weather forecasting models apply uniform computation across all spatial tokens, even though nearby atmospheric grid points often contain similar values and large…
CTR-LoRA: Curvature-Aware and Trust-Region Guided Low-Rank Adaptation for Large Language Models
Zhuxuanzi Wang, Mingqiao Mo, Xi Xiao +6
Parameter-efficient fine-tuning (PEFT) has become the standard approach for adapting large language models under limited compute and memory budgets. Although previous methods impro…
HyperAdaLoRA: Accelerating LoRA Rank Allocation During Training via Hypernetworks without Sacrificing Performance
Hao Zhang, Zhenjia Li, Runfeng Bao +8
Parameter-Efficient Fine-Tuning (PEFT), especially Low-Rank Adaptation (LoRA), has emerged as a promising approach to fine-tuning large language models(LLMs) while reducing computa…
Sensitivity-LoRA: Low-Load Sensitivity-Based Fine-Tuning for Large Language Models
Hao Zhang, Bo Huang, Zhenjia Li +6
Large Language Models (LLMs) have transformed both everyday life and scientific research. However, adapting LLMs from general-purpose models to specialized tasks remains challengin…
MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding
Yuxiang Wei, Yanteng Zhang, Xi Xiao +3
Decoding visual experiences from fMRI offers a powerful avenue to understand human perception and develop advanced brain-computer interfaces. However, current progress often priori…
ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling
Xiao Wang, Jong-Youl Choi, Takuya Kurihaya +15
Sparse observations and coarse-resolution climate models limit effective regional decision-making, underscoring the need for robust downscaling. However, existing AI methods strugg…
CAD-VAE: Leveraging Correlation-Aware Latents for Comprehensive Fair Disentanglement
Chenrui Ma, Xi Xiao, Tianyang Wang +2
While deep generative models have significantly advanced representation learning, they may inherit or amplify biases and fairness issues by encoding sensitive attributes alongside…
E2CB2former: Effecitve and Explainable Transformer for CB2 Receptor Ligand Activity Prediction
Jiacheng Xie, Yingrui Ji, Linghuan Zeng +5
Accurate prediction of CB2 receptor ligand activity is pivotal for advancing drug discovery targeting this receptor, which is implicated in inflammation, pain management, and neuro…
HGTDP-DTA: Hybrid Graph-Transformer with Dynamic Prompt for Drug-Target Binding Affinity Prediction
Xi Xiao, Wentao Wang, Jiacheng Xie +5
Drug target binding affinity (DTA) is a key criterion for drug screening. Existing experimental methods are time-consuming and rely on limited structural and domain information. Wh…