b'James Zou'

research

∙ 09/14/2023

Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions

Training large language models to follow instructions makes them perform...

0 Federico Bianchi, et al. ∙

research

∙ 08/31/2023

Large language models in medicine: the potentials and pitfalls

Large language models (LLMs) have been applied to tasks in healthcare, r...

0 Jesutofunmi A. Omiye, et al. ∙

research

∙ 08/03/2023

Is your data alignable? Principled and interpretable alignability testing and integration of single-cell data

Single-cell data integration can provide a comprehensive molecular view ...

0 Rong Ma, et al. ∙

research

∙ 07/18/2023

How is ChatGPT's behavior changing over time?

GPT-3.5 and GPT-4 are the two most widely used large language model (LLM...

0 Lingjiao Chen, et al. ∙

research

∙ 07/06/2023

What Should Data Science Education Do with Large Language Models?

The rapid advances of large language models (LLMs), such as ChatGPT, are...

0 Xinming Tu, et al. ∙

research

∙ 06/18/2023

OpenDataVal: a Unified Benchmark for Data Valuation

Assessing the quality and impact of individual data points is critical f...

0 Kevin Fu Jiang, et al. ∙

research

∙ 06/14/2023

TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter

Recent progress in generative artificial intelligence (gen-AI) has enabl...

0 Yiqun Chen, et al. ∙

research

∙ 06/13/2023

ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations

As generative AI becomes more prevalent, it is important to study how hu...

0 Kailas Vodrahalli, et al. ∙

research

∙ 06/08/2023

Factorized Contrastive Learning: Going Beyond Multi-view Redundancy

In a wide range of multimodal tasks, contrastive learning has become a p...

0 Paul Pu Liang, et al. ∙

research

∙ 05/29/2023

Beyond Confidence: Reliable Models Should Also Consider Atypicality

While most machine learning models can provide confidence in their predi...

0 Mert Yüksekgönül, et al. ∙

research

∙ 05/27/2023

Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models

Language models have been shown to exhibit positive scaling, where perfo...

0 Yuhui Zhang, et al. ∙

research

∙ 05/09/2023

FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

There is a rapidly growing number of large language models (LLMs) that u...

0 Lingjiao Chen, et al. ∙

research

∙ 05/04/2023

On the nonlinear correlation of ML performance between data subpopulations

Understanding the performance of machine learning (ML) models across div...

0 Weixin Liang, et al. ∙

research

∙ 05/01/2023

Discover and Cure: Concept-aware Mitigation of Spurious Correlation

Deep neural networks often rely on spurious correlations to make predict...

0 Shirley Wu, et al. ∙

research

∙ 04/29/2023

Data-Driven Subgroup Identification for Linear Regression

Medical studies frequently require to extract the relationship between e...

0 Zachary Izzo, et al. ∙

research

∙ 04/16/2023

Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value

Data valuation is a powerful framework for providing statistical insight...

0 Yongchan Kwon, et al. ∙

research

∙ 04/08/2023

Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks

As machine learning has been deployed ubiquitously across applications i...

0 Yuzhen Mao, et al. ∙

research

∙ 04/06/2023

GPT detectors are biased against non-native English writers

The rapid adoption of generative language models has brought about subst...

0 Weixin Liang, et al. ∙

research

∙ 02/13/2023

Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data

Language-supervised vision models have recently attracted great attentio...

0 Ryumei Nakada, et al. ∙

research

∙ 02/08/2023

Diagnosing and Rectifying Vision Models using Language

Recent multi-modal contrastive learning models have demonstrated the abi...

0 Yuhui Zhang, et al. ∙

research

∙ 02/01/2023

SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained model debugging and analysis

For the deployment of artificial intelligence (AI) in high-risk settings...

11 Roxana Daneshjou, et al. ∙

research

∙ 11/28/2022

FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee

Algorithmic fairness plays an increasingly critical role in machine lear...

0 Puheng Li, et al. ∙

research

∙ 11/12/2022

Provable Membership Inference Privacy

In applications involving sensitive data, such as finance and healthcare...

0 Zachary Izzo, et al. ∙

research

∙ 11/07/2022

Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale

Machine learning models are now able to convert user-written text descri...

0 Federico Bianchi, et al. ∙

research

∙ 10/25/2022

A Spectral Method for Assessing and Combining Multiple Data Visualizations

Dimension reduction and data visualization aim to project a high-dimensi...

0 Rong Ma, et al. ∙

research

∙ 10/20/2022

Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise

The existence of spurious correlations such as image backgrounds in the ...

0 Haotian Ye, et al. ∙

research

∙ 10/11/2022

SEAL : Interactive Tool for Systematic Error Analysis and Labeling

With the advent of Transformers, large language models (LLMs) have satur...

0 Nazneen Rajani, et al. ∙

research

∙ 10/11/2022

C-Mixup: Improving Generalization in Regression

Improving the generalization of deep networks is an important open chall...

7 Huaxiu Yao, et al. ∙

research

∙ 10/11/2022

Knowledge-Driven New Drug Recommendation

Drug recommendation assists doctors in prescribing personalized medicati...

24 Zhenbang Wu, et al. ∙

research

∙ 10/04/2022

When and why vision-language models behave like bags-of-words, and what to do about it?

Despite the success of large vision and language models (VLMs) in many d...

0 Mert Yüksekgönül, et al. ∙

research

∙ 10/03/2022

Data Budgeting for Machine Learning

Data is the fuel powering AI and creates tremendous value for many domai...

0 Xinyi Zhao, et al. ∙

research

∙ 10/02/2022

Ensembling improves stability and power of feature selection for deep learning models

With the growing adoption of deep learning models in different real-worl...

11 Prashnna K Gyawali, et al. ∙

research

∙ 09/27/2022

WeightedSHAP: analyzing and improving Shapley based feature attributions

Shapley value is a popular approach for measuring the influence of indiv...

0 Yongchan Kwon, et al. ∙

research

∙ 09/18/2022

HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions

Commercial ML APIs offered by providers such as Google, Amazon and Micro...

8 Lingjiao Chen, et al. ∙

research

∙ 09/18/2022

Estimating and Explaining Model Performance When Both Covariates and Labels Shift

Deployed machine learning (ML) models often encounter new user data that...

3 Lingjiao Chen, et al. ∙

research

∙ 09/12/2022

Development and Clinical Evaluation of an AI Support Tool for Improving Telemedicine Photo Quality

Telemedicine utilization was accelerated during the COVID-19 pandemic, a...

9 Kailas Vodrahalli, et al. ∙

research

∙ 07/20/2022

DataPerf: Benchmarks for Data-Centric AI Development

Machine learning (ML) research has generally focused on models, while th...

17 Mark Mazumder, et al. ∙

research

∙ 06/30/2022

GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language

Helping end users comprehend the abstract distribution shifts can greatl...

0 Zhiying Zhu, et al. ∙

research

∙ 06/06/2022

FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data

Algorithmic fairness plays an important role in machine learning and imp...

0 Zhun Deng, et al. ∙

research

∙ 05/31/2022

Post-hoc Concept Bottleneck Models

Concept Bottleneck Models (CBMs) map the inputs onto a set of interpreta...

0 Mert Yüksekgönül, et al. ∙

research

∙ 05/11/2022

A Unified f-divergence Framework Generalizing VAE and GAN

Developing deep generative models that flexibly incorporate diverse meas...

0 Jaime Roquero Gimenez, et al. ∙

research

∙ 05/10/2022

Improving genetic risk prediction across diverse population by disentangling ancestry representations

Risk prediction models using genetic data have seen increasing traction ...

8 Prashnna K Gyawali, et al. ∙

research

∙ 03/24/2022

Domino: Discovering Systematic Errors with Cross-Modal Embeddings

Machine learning models that achieve high overall accuracy often make sy...

4 Sabri Eyuboglu, et al. ∙

research

∙ 03/15/2022

Disparities in Dermatology AI Performance on a Diverse, Curated Clinical Image Set

Access to dermatological care is a major issue, with an estimated 3 bill...

6 Roxana Daneshjou, et al. ∙

research

∙ 03/03/2022

Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning

We present modality gap, an intriguing geometric phenomenon of the repre...

15 Weixin Liang, et al. ∙

research

∙ 02/14/2022

MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts

Understanding the performance of machine learning models across diverse ...

0 Weixin Liang, et al. ∙

research

∙ 02/12/2022

Uncalibrated Models Can Improve Human-AI Collaboration

In many practical applications of AI, an AI model is used as a decision ...

0 Kailas Vodrahalli, et al. ∙

research

∙ 01/26/2022

Competition over data: how does data purchase affect users?

As machine learning (ML) is deployed by many competing service providers...

0 Yongchan Kwon, et al. ∙

research

∙ 01/04/2022

Submix: Practical Private Prediction for Large-Scale Language Models

Recent data-extraction attacks have exposed that language models can mem...

0 Antonio Ginart, et al. ∙

research

∙ 01/02/2022

Improving Out-of-Distribution Robustness via Selective Augmentation

Machine learning algorithms typically assume that training and test exam...

109 Huaxiu Yao, et al. ∙

James Zou

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