b'Q Vera Liao'

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Pin-Yu Chen
183 publications
Maarten de Rijke
166 publications
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106 publications
Adrian Weller
101 publications
Huamin Qu
86 publications
Pierre-Yves Oudeyer
70 publications
Kush R. Varshney
68 publications
Hal Daumé III
56 publications
Karthikeyan Shanmugam
50 publications
Chenhao Tan
48 publications
Mark O. Riedl
46 publications

research

∙ 06/02/2023

AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap

The rise of powerful large language models (LLMs) brings about tremendou...

0 Q Vera Liao, et al. ∙

research

∙ 06/01/2023

Rethinking Model Evaluation as Narrowing the Socio-Technical Gap

The recent development of generative and large language models (LLMs) po...

0 Q Vera Liao, et al. ∙

research

∙ 05/24/2023

Evaluating NLG Evaluation Metrics: A Measurement Theory Perspective

We address the fundamental challenge in Natural Language Generation (NLG...

0 Ziang Xiao, et al. ∙

research

∙ 04/17/2023

Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling

Data storytelling plays an important role in data workers' daily jobs si...

0 Haotian Li, et al. ∙

research

∙ 04/17/2023

Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Coding

Qualitative analysis of textual contents unpacks rich and valuable infor...

0 Ziang Xiao, et al. ∙

research

∙ 03/13/2023

Sensing Wellbeing in the Workplace, Why and For Whom? Envisioning Impacts with Organizational Stakeholders

With the heightened digitization of the workplace, alongside the rise of...

0 Anna Kawakami, et al. ∙

research

∙ 02/22/2023

fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks

To design with AI models, user experience (UX) designers must assess the...

0 Steven Moore, et al. ∙

research

∙ 02/21/2023

Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience

Despite the widespread use of artificial intelligence (AI), designing us...

0 Q Vera Liao, et al. ∙

research

∙ 02/16/2023

Human-Centered Responsible Artificial Intelligence: Current Future Trends

In recent years, the CHI community has seen significant growth in resear...

0 Mohammad Tahaei, et al. ∙

research

∙ 02/14/2023

Generation Probabilities Are Not Enough: Exploring the Effectiveness of Uncertainty Highlighting in AI-Powered Code Completions

Large-scale generative models enabled the development of AI-powered code...

0 Helena Vasconcelos, et al. ∙

research

∙ 01/25/2023

Powering an AI Chatbot with Expert Sourcing to Support Credible Health Information Access

During a public health crisis like the COVID-19 pandemic, a credible and...

0 Ziang Xiao, et al. ∙

research

∙ 01/23/2023

Selective Explanations: Leveraging Human Input to Align Explainable AI

While a vast collection of explainable AI (XAI) algorithms have been dev...

0 Vivian Lai, et al. ∙

research

∙ 01/18/2023

Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations

AI explanations are often mentioned as a way to improve human-AI decisio...

0 Valerie Chen, et al. ∙

research

∙ 11/12/2022

Seamful XAI: Operationalizing Seamful Design in Explainable AI

Mistakes in AI systems are inevitable, arising from both technical limit...

0 Upol Ehsan, et al. ∙

research

∙ 06/22/2022

Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI

Recent years have seen a surge of interest in the field of explainable A...

15 Q Vera Liao, et al. ∙

research

∙ 04/29/2022

Designing for Responsible Trust in AI Systems: A Communication Perspective

Current literature and public discourse on "trust in AI" are often focus...

7 Q Vera Liao, et al. ∙

research

∙ 04/25/2022

Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation

Despite impressive performance in many benchmark datasets, AI models can...

4 Vivian Lai, et al. ∙

research

∙ 02/10/2022

Investigating Explainability of Generative AI for Code through Scenario-based Design

What does it mean for a generative AI model to be explainable? The emerg...

16 Jiao Sun, et al. ∙

research

∙ 12/21/2021

Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies

As AI systems demonstrate increasingly strong predictive performance, th...

15 Vivian Lai, et al. ∙

research

∙ 10/20/2021

Human-Centered Explainable AI (XAI): From Algorithms to User Experiences

As a technical sub-field of artificial intelligence (AI), explainable AI...

44 Q Vera Liao, et al. ∙

research

∙ 09/24/2021

AI Explainability 360: Impact and Design

As artificial intelligence and machine learning algorithms become increa...

46 Vijay Arya, et al. ∙

research

∙ 07/28/2021

The Who in Explainable AI: How AI Background Shapes Perceptions of AI Explanations

Explainability of AI systems is critical for users to take informed acti...

19 Upol Ehsan, et al. ∙

research

∙ 06/02/2021

Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI

In this paper, we describe an open source Python toolkit named Uncertain...

107 Soumya Ghosh, et al. ∙

research

∙ 04/09/2021

Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML

Automated Machine Learning (AutoML) is a rapidly growing set of technolo...

6 Shweta Narkar, et al. ∙

research

∙ 04/08/2021

Question-Driven Design Process for Explainable AI User Experiences

A pervasive design issue of AI systems is their explainability–how to pr...

8 Q Vera Liao, et al. ∙

research

∙ 03/27/2021

A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms

Given that there are a variety of stakeholders involved in, and affected...

0 Ana Lucic, et al. ∙

research

∙ 01/29/2021

Facilitating Knowledge Sharing from Domain Experts to Data Scientists for Building NLP Models

Data scientists face a steep learning curve in understanding a new domai...

21 Soya Park, et al. ∙

research

∙ 01/12/2021

Expanding Explainability: Towards Social Transparency in AI systems

As AI-powered systems increasingly mediate consequential decision-making...

27 Upol Ehsan, et al. ∙

research

∙ 01/07/2021

How Much Automation Does a Data Scientist Want?

Data science and machine learning (DS/ML) are at the heart of the recent...

54 Dakuo Wang, et al. ∙

research

∙ 11/15/2020

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty

Transparency of algorithmic systems entails exposing system properties t...

6 Umang Bhatt, et al. ∙

research

∙ 09/06/2020

Active Learning++: Incorporating Annotator's Rationale using Local Model Explanation

We propose a new active learning (AL) framework, Active Learning++, whic...

12 Bhavya Ghai, et al. ∙

research

∙ 04/04/2020

Measuring Social Biases of Crowd Workers using Counterfactual Queries

Social biases based on gender, race, etc. have been shown to pollute mac...

1 Bhavya Ghai, et al. ∙

research

∙ 01/24/2020

Explainable Active Learning (XAL): An Empirical Study of How Local Explanations Impact Annotator Experience

Active Learning (AL) is a human-in-the-loop Machine Learning paradigm fa...

43 Bhavya Ghai, et al. ∙

research

∙ 01/08/2020

Questioning the AI: Informing Design Practices for Explainable AI User Experiences

A surge of interest in explainable AI (XAI) has led to a vast collection...

0 Q Vera Liao, et al. ∙

research

∙ 01/07/2020

Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making

Today, AI is being increasingly used to help human experts make decision...

0 Yunfeng Zhang, et al. ∙

research

∙ 12/13/2019

Enabling Value Sensitive AI Systems through Participatory Design Fictions

Two general routes have been followed to develop artificial agents that ...

0 Q Vera Liao, et al. ∙

research

∙ 09/06/2019

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

As artificial intelligence and machine learning algorithms make further ...

36 Vijay Arya, et al. ∙

research

∙ 05/25/2019

Tell Me About Yourself: Using an AI-Powered Chatbot to Conduct Conversational Surveys

The rise of increasingly more powerful chatbots offers a new way to coll...

0 Ziang Xiao, et al. ∙

research

∙ 01/23/2019

Explaining Models: An Empirical Study of How Explanations Impact Fairness Judgment

Ensuring fairness of machine learning systems is a human-in-the-loop pro...

0 Jonathan Dodge, et al. ∙

research

∙ 12/14/2018

Bootstrapping Conversational Agents With Weak Supervision

Many conversational agents in the market today follow a standard bot dev...

0 Neil Mallinar, et al. ∙

research

∙ 08/04/2017

A Measure for Dialog Complexity and its Application in Streamlining Service Operations

Dialog is a natural modality for interaction between customers and busin...

0 Q Vera Liao, et al. ∙

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