Search Results for author: Xuan Lin

Found 11 papers, 4 papers with code

Property Enhanced Instruction Tuning for Multi-task Molecule Generation with Large Language Models

1 code implementation24 Dec 2024 Xuan Lin, Long Chen, Yile Wang, Xiangxiang Zeng, Philip S. Yu

In the first step, we use textual descriptions, SMILES, and biochemical properties as multimodal inputs to pre-train a model called PEIT-GEN, by aligning multi-modal representations to synthesize instruction data.

Machine Translation Molecular Property Prediction +3

S$^2$DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph Completion

no code implementations20 Dec 2024 Tengfei Ma, Yujie Chen, Liang Wang, Xuan Lin, Bosheng Song, Xiangxiang Zeng

These results demonstrate the effectiveness of S$^2$DN in preserving semantic consistency and enhancing the robustness of filtering out unreliable interactions in contaminated KGs.

Denoising Inductive knowledge graph completion

Y-Mol: A Multiscale Biomedical Knowledge-Guided Large Language Model for Drug Development

no code implementations15 Oct 2024 Tengfei Ma, Xuan Lin, Tianle Li, Chaoyi Li, Long Chen, Peng Zhou, Xibao Cai, Xinyu Yang, Daojian Zeng, Dongsheng Cao, Xiangxiang Zeng

Besides, Y-Mol offers a set of LLM paradigms that can autonomously execute the downstream tasks across the entire process of drug development, including virtual screening, drug design, pharmacological properties prediction, and drug-related interaction prediction.

Drug Design Knowledge Graphs +2

Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction

1 code implementation8 Jun 2023 Xuan Lin, Lichang Dai, Yafang Zhou, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen, Bosheng Song, Philip S. Yu, Xiangxiang Zeng

Recent advances and achievements of artificial intelligence (AI) as well as deep and graph learning models have established their usefulness in biomedical applications, especially in drug-drug interactions (DDIs).

Drug Discovery Graph Learning +2

ViT-TTS: Visual Text-to-Speech with Scalable Diffusion Transformer

no code implementations22 May 2023 Huadai Liu, Rongjie Huang, Xuan Lin, Wenqiang Xu, Maozong Zheng, Hong Chen, Jinzheng He, Zhou Zhao

To mitigate the data scarcity in learning visual acoustic information, we 1) introduce a self-supervised learning framework to enhance both the visual-text encoder and denoiser decoder; 2) leverage the diffusion transformer scalable in terms of parameters and capacity to learn visual scene information.

Decoder Denoising +2

AntCritic: Argument Mining for Free-Form and Visually-Rich Financial Comments

no code implementations20 Aug 2022 Huadai Liu, Wenqiang Xu, Xuan Lin, Jingjing Huo, Hong Chen, Zhou Zhao

Argument mining aims to detect all possible argumentative components and identify their relationships automatically.

Argument Mining Relation Prediction

Simultaneous Contact-Rich Grasping and Locomotion via Distributed Optimization Enabling Free-Climbing for Multi-Limbed Robots

no code implementations4 Jul 2022 Yuki Shirai, Xuan Lin, Alexander Schperberg, Yusuke Tanaka, Hayato Kato, Varit Vichathorn, Dennis Hong

While motion planning of locomotion for legged robots has shown great success, motion planning for legged robots with dexterous multi-finger grasping is not mature yet.

Distributed Optimization Motion Planning

AntPivot: Livestream Highlight Detection via Hierarchical Attention Mechanism

no code implementations10 Jun 2022 Yang Zhao, Xuan Lin, Wenqiang Xu, Maozong Zheng, Zhengyong Liu, Zhou Zhao

In recent days, streaming technology has greatly promoted the development in the field of livestream.

Highlight Detection

DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction

1 code implementation31 Mar 2020 Xuan Lin

Recently, with the increasing amount of affinity data available and the success of deep representation learning models on various domains, deep learning techniques have been applied to DTA prediction.

Drug Discovery Representation Learning

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