Weixin Liang | DeepAI

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∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 11/15/2021

Disparities in Dermatology AI: Assessments Using Diverse Clinical Images

More than 3 billion people lack access to care for skin disease. AI diag...

10 Roxana Daneshjou, et al. ∙

∙ 06/01/2021

HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations

Open-domain dialog systems have a user-centric goal: to provide humans w...

0 Weixin Liang, et al. ∙

∙ 04/20/2021

GraghVQA: Language-Guided Graph Neural Networks for Graph-based Visual Question Answering

Images are more than a collection of objects or attributes – they repres...

0 Weixin Liang, et al. ∙

∙ 11/21/2020

LRTA: A Transparent Neural-Symbolic Reasoning Framework with Modular Supervision for Visual Question Answering

The predominant approach to visual question answering (VQA) relies on en...

0 Weixin Liang, et al. ∙

∙ 11/21/2020

Neural Group Testing to Accelerate Deep Learning

Recent advances in deep learning have made the use of large, deep neural...

0 Weixin Liang, et al. ∙

∙ 09/22/2020

ALICE: Active Learning with Contrastive Natural Language Explanations

Training a supervised neural network classifier typically requires many ...

15 Weixin Liang, et al. ∙

∙ 05/21/2020

Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation

Open Domain dialog system evaluation is one of the most important challe...

0 Weixin Liang, et al. ∙

∙ 01/02/2020

DAWSON: A Domain Adaptive Few Shot Generation Framework

Training a Generative Adversarial Networks (GAN) for a new domain from s...

21 Weixin Liang, et al. ∙

∙ 09/12/2019

MOSS: End-to-End Dialog System Framework with Modular Supervision

A major bottleneck in training end-to-end task-oriented dialog system is...

1 Weixin Liang, et al. ∙

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