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Author: 4055

Results: 15

Human-AI collaboration; Human-AI collaboration

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Human-AI Collaboration / Images in AI

Interpreting and Explaining AI

Paper Title	Authors	Research Topics
	MF	Human-AI collaboration; Human-AI collaboration
	JS
	VL
	SN
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
	SP
emoji_events	UE
	ZA	Human-AI Collaboration / Images in AI
	BG	Interpreting and Explaining AI
emoji_events	QL
	MM
	ZA
	JD
	YZ
	AS
	QL

Papers

Human-AI Collaboration for UX Evaluation: Effects of Explanation and Synchronization

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

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

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

Learn AI Coding at CodeNow

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

Expanding Explainability: Towards Social Transparency in AI systems

Human-AI Collaboration in a Cooperative Game Setting: Measuring Social Perception and Outcomes

Explainable Active Learning (XAL): Toward AI Explanations as Interfaces for Machine Teachers

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

How Data Science Workers Work with Data: Discovery, Capture, Curation, Design, Creation

Resilient Chatbots: Repair Strategy Preferences for Conversational Breakdowns

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

Towards an optimal dialog strategy for information retrieval using both open-ended and close-ended questions

Face Value? Exploring the Effects of Embodiment for a Group Facilitation Agent

All Work and No Play? Conversations with a Question-and-Answer Chatbot in the Wild

Human-AI Collaboration for UX Evaluation: Effects of Explanation and Synchronization

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

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

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

Learn AI Coding at CodeNow

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

Expanding Explainability: Towards Social Transparency in AI systems

Human-AI Collaboration in a Cooperative Game Setting: Measuring Social Perception and Outcomes

Explainable Active Learning (XAL): Toward AI Explanations as Interfaces for Machine Teachers

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

How Data Science Workers Work with Data: Discovery, Capture, Curation, Design, Creation

Resilient Chatbots: Repair Strategy Preferences for Conversational Breakdowns

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

Towards an optimal dialog strategy for information retrieval using both open-ended and close-ended questions

Face Value? Exploring the Effects of Embodiment for a Group Facilitation Agent

All Work and No Play? Conversations with a Question-and-Answer Chatbot in the Wild

Papers

Human-AI Collaboration for UX Evaluation: Effects of Explanation and Synchronization

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

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

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

Learn AI Coding at CodeNow

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

Expanding Explainability: Towards Social Transparency in AI systems

Human-AI Collaboration in a Cooperative Game Setting: Measuring Social Perception and Outcomes

Explainable Active Learning (XAL): Toward AI Explanations as Interfaces for Machine Teachers

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

How Data Science Workers Work with Data: Discovery, Capture, Curation, Design, Creation

Resilient Chatbots: Repair Strategy Preferences for Conversational Breakdowns

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

Towards an optimal dialog strategy for information retrieval using both open-ended and close-ended questions

Face Value? Exploring the Effects of Embodiment for a Group Facilitation Agent

All Work and No Play? Conversations with a Question-and-Answer Chatbot in the Wild

Human-AI Collaboration for UX Evaluation: Effects of Explanation and Synchronization

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

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

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

Learn AI Coding at CodeNow

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

Expanding Explainability: Towards Social Transparency in AI systems

Human-AI Collaboration in a Cooperative Game Setting: Measuring Social Perception and Outcomes

Explainable Active Learning (XAL): Toward AI Explanations as Interfaces for Machine Teachers

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

How Data Science Workers Work with Data: Discovery, Capture, Curation, Design, Creation

Resilient Chatbots: Repair Strategy Preferences for Conversational Breakdowns

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

Towards an optimal dialog strategy for information retrieval using both open-ended and close-ended questions

Face Value? Exploring the Effects of Embodiment for a Group Facilitation Agent

All Work and No Play? Conversations with a Question-and-Answer Chatbot in the Wild