Bingsheng Yao

Orcid: 0009-0004-8329-4610

According to our database1, Bingsheng Yao authored at least 29 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., March, 2024

Human-Centered Privacy Research in the Age of Large Language Models.
CoRR, 2024

Exploring Parent's Needs for Children-Centered AI to Support Preschoolers' Storytelling and Reading Activities.
CoRR, 2024

Who Changed the Destiny of Rural Students, and How?: Unpacking ICT-Mediated Remote Education in Rural China.
CoRR, 2024

2023
Bergeron: Combating Adversarial Attacks through a Conscience-Based Alignment Framework.
CoRR, 2023

Human Still Wins over LLM: An Empirical Study of Active Learning on Domain-Specific Annotation Tasks.
CoRR, 2023

More Samples or More Prompt Inputs? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering.
CoRR, 2023

FairytaleCQA: Integrating a Commonsense Knowledge Graph into Children's Storybook Narratives.
CoRR, 2023

'Don't Get Too Technical with Me': A Discourse Structure-Based Framework for Science Journalism.
CoRR, 2023

"Mango Mango, How to Let The Lettuce Dry Without A Spinner?": Exploring User Perceptions of Using An LLM-Based Conversational Assistant Toward Cooking Partner.
CoRR, 2023

LLM-Powered Conversational Voice Assistants: Interaction Patterns, Opportunities, Challenges, and Design Guidelines.
CoRR, 2023

Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis.
CoRR, 2023

"It's a Fair Game", or Is It? Examining How Users Navigate Disclosure Risks and Benefits When Using LLM-Based Conversational Agents.
CoRR, 2023

Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model.
CoRR, 2023

Beyond Labels: Empowering Human with Natural Language Explanations through a Novel Active-Learning Architecture.
CoRR, 2023

Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

'Don't Get Too Technical with Me': A Discourse Structure-Based Framework for Automatic Science Journalism.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Are Human Explanations Always Helpful? Towards Objective Evaluation of Human Natural Language Explanations.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
NECE: Narrative Event Chain Extraction Toolkit.
CoRR, 2022

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code.
CoRR, 2022

Efficient Long Sequence Encoding via Synchronization.
CoRR, 2022

A Corpus for Commonsense Inference in Story Cloze Test.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement.
Proceedings of the CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April 2022, 2022

It is AI's Turn to Ask Humans a Question: Question-Answer Pair Generation for Children's Story Books.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Fantastic Questions and Where to Find Them: FairytaleQA - An Authentic Dataset for Narrative Comprehension.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study.
Trans. Assoc. Comput. Linguistics, 2021

It is AI's Turn to Ask Human a Question: Question and Answer Pair Generation for Children Storybooks in FairytaleQA Dataset.
CoRR, 2021

2020
Trust in AutoML: exploring information needs for establishing trust in automated machine learning systems.
Proceedings of the IUI '20: 25th International Conference on Intelligent User Interfaces, 2020

Frustratingly Hard Evidence Retrieval for QA Over Books.
Proceedings of the First Joint Workshop on Narrative Understanding, Storylines, and Events, 2020


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