Search Results for author: Kexin Huang

Found 22 papers, 12 papers with code

Flames: Benchmarking Value Alignment of Chinese Large Language Models

no code implementations12 Nov 2023 Kexin Huang, Xiangyang Liu, Qianyu Guo, Tianxiang Sun, Jiawei Sun, Yaru Wang, Zeyang Zhou, Yixu Wang, Yan Teng, Xipeng Qiu, Yingchun Wang, Dahua Lin

To efficiently evaluate new models on the benchmark, we develop a specified scorer capable of scoring LLMs across multiple dimensions, achieving an accuracy of 77. 4%.

Benchmarking Fairness

Fake Alignment: Are LLMs Really Aligned Well?

no code implementations10 Nov 2023 Yixu Wang, Yan Teng, Kexin Huang, Chengqi Lyu, Songyang Zhang, Wenwei Zhang, Xingjun Ma, Yu-Gang Jiang, Yu Qiao, Yingchun Wang

To address this, we introduce the Fake alIgNment Evaluation (FINE) framework and two novel metrics--Consistency Score (CS) and Consistent Safety Score (CSS), which jointly assess two complementary forms of evaluation to quantify fake alignment and obtain corrected performance estimates.


Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph

no code implementations7 Jun 2023 Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec

However, for tabular datasets with extremely high $d$-dimensional features but limited $n$ samples (i. e. $d \gg n$), machine learning models struggle to achieve strong performance due to the risk of overfitting.

Inductive Bias

Learn to Explore: on Bootstrapping Interactive Data Exploration with Meta-learning

no code implementations7 Dec 2022 Yukun Cao, Xike Xie, Kexin Huang

The process of data exploration can be viewed as the process of training a classifier, which determines whether a database tuple is interesting to a user.

Active Learning Efficient Exploration +1

TuneUp: A Simple Improved Training Strategy for Graph Neural Networks

no code implementations26 Oct 2022 Weihua Hu, Kaidi Cao, Kexin Huang, Edward W Huang, Karthik Subbian, Kenji Kawaguchi, Jure Leskovec

Extensive evaluation of TuneUp on five diverse GNN architectures, three types of prediction tasks, and both transductive and inductive settings shows that TuneUp significantly improves the performance of the base GNN on tail nodes, while often even improving the performance on head nodes.

Data Augmentation

Machine Learning Applications for Therapeutic Tasks with Genomics Data

no code implementations3 May 2021 Kexin Huang, Cao Xiao, Lucas M. Glass, Cathy W. Critchlow, Greg Gibson, Jimeng Sun

Thanks to the increasing availability of genomics and other biomedical data, many machine learning approaches have been proposed for a wide range of therapeutic discovery and development tasks.

BIG-bench Machine Learning

Graph Representation Learning in Biomedicine

no code implementations11 Apr 2021 Michelle M. Li, Kexin Huang, Marinka Zitnik

Biomedical networks (or graphs) are universal descriptors for systems of interacting elements, from molecular interactions and disease co-morbidity to healthcare systems and scientific knowledge.

BIG-bench Machine Learning Graph Representation Learning

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development

2 code implementations18 Feb 2021 Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik

Here, we introduce Therapeutics Data Commons (TDC), the first unifying platform to systematically access and evaluate machine learning across the entire range of therapeutics.

BIG-bench Machine Learning Drug Discovery

HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data

1 code implementation8 Feb 2021 Tianfan Fu, Kexin Huang, Cao Xiao, Lucas M. Glass, Jimeng Sun

Next, these embeddings will be fed into the knowledge embedding module to generate knowledge embeddings that are pretrained using external knowledge on pharmaco-kinetic properties and trial risk from the web.


An Interpretable End-to-end Fine-tuning Approach for Long Clinical Text

no code implementations12 Nov 2020 Kexin Huang, Sankeerth Garapati, Alexander S. Rich

Unstructured clinical text in EHRs contains crucial information for applications including decision support, trial matching, and retrospective research.

text-classification Text Classification

MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning

1 code implementation5 Oct 2020 Kexin Huang, Tianfan Fu, Dawood Khan, Ali Abid, Ali Abdalla, Abubakar Abid, Lucas M. Glass, Marinka Zitnik, Cao Xiao, Jimeng Sun

The efficacy of a drug depends on its binding affinity to the therapeutic target and pharmacokinetics.

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization

1 code implementation4 Oct 2020 Yue Yu, Kexin Huang, Chao Zhang, Lucas M. Glass, Jimeng Sun, Cao Xiao

Furthermore, most previous works focus on binary DDI prediction whereas the multi-typed DDI pharmacological effect prediction is a more meaningful but harder task.

Data Integration Knowledge Graphs

Graph Meta Learning via Local Subgraphs

1 code implementation NeurIPS 2020 Kexin Huang, Marinka Zitnik

G-Meta learns how to quickly adapt to a new task using only a handful of nodes or edges in the new task and does so by learning from data points in other graphs or related, albeit disjoint label sets.

Few-Shot Learning

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks

1 code implementation30 Apr 2020 Kexin Huang, Cao Xiao, Lucas Glass, Marinka Zitnik, Jimeng Sun

Here, we present SkipGNN, a graph neural network approach for the prediction of molecular interactions.

MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction

1 code implementation23 Apr 2020 Kexin Huang, Cao Xiao, Lucas Glass, Jimeng Sun

Drug target interaction (DTI) prediction is a foundational task for in silico drug discovery, which is costly and time-consuming due to the need of experimental search over large drug compound space.

Drug Discovery molecular representation +1

ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission

2 code implementations10 Apr 2019 Kexin Huang, Jaan Altosaar, Rajesh Ranganath

Clinical notes contain information about patients that goes beyond structured data like lab values and medications.

Readmission Prediction

Cannot find the paper you are looking for? You can Submit a new open access paper.