Search Results for author: Dakuo Wang

Found 53 papers, 17 papers with code

FairytaleCQA: Integrating a Commonsense Knowledge Graph into Children's Storybook Narratives

no code implementations16 Nov 2023 Jiaju Chen, Yuxuan Lu, Shao Zhang, Bingsheng Yao, Yuanzhe Dong, Ying Xu, Yunyao Li, Qianwen Wang, Dakuo Wang, Yuling Sun

AI models (including LLM) often rely on narrative question-answering (QA) datasets to provide customized QA functionalities to support downstream children education applications; however, existing datasets only include QA pairs that are grounded within the given storybook content, but children can learn more when teachers refer the storybook content to real-world knowledge (e. g., commonsense knowledge).

Question Answering World Knowledge

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

no code implementations16 Nov 2023 Bingsheng Yao, Guiming Chen, Ruishi Zou, Yuxuan Lu, Jiachen Li, Shao Zhang, Sijia Liu, James Hendler, Dakuo Wang

While most existing works on LLM prompt-engineering focus only on how to select a better set of data samples inside one single prompt input (In-Context Learning or ICL), why can't we design and leverage multiple prompt inputs together to further improve the LLM performance?

Prompt Engineering

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

no code implementations16 Nov 2023 Yuxuan Lu, Bingsheng Yao, Shao Zhang, Yun Wang, Peng Zhang, Tun Lu, Toby Jia-Jun Li, Dakuo Wang

Large Language Models (LLMs) have demonstrated considerable advances, and several claims have been made about their exceeding human performance.

Active Learning

Bergeron: Combating Adversarial Attacks through a Conscience-Based Alignment Framework

no code implementations16 Nov 2023 Matthew Pisano, Peter Ly, Abraham Sanders, Bingsheng Yao, Dakuo Wang, Tomek Strzalkowski, Mei Si

We do this by monitoring for and correcting potentially harmful text within both the prompt inputs and the generated outputs of the primary LLM.

Is a Seat at the Table Enough? Engaging Teachers and Students in Dataset Specification for ML in Education

no code implementations9 Nov 2023 Mei Tan, Hansol Lee, Dakuo Wang, Hariharan Subramonyam

To overcome these challenges and fully utilize the potential of ML in education, software practitioners need to work closely with educators and students to fully understand the context of the data (the backbone of ML applications) and collaboratively define the ML data specifications.


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

1 code implementation23 Oct 2023 Ronald Cardenas, Bingsheng Yao, Dakuo Wang, Yufang Hou

Science journalism refers to the task of reporting technical findings of a scientific paper as a less technical news article to the general public audience.

Will the Prince Get True Love's Kiss? On the Model Sensitivity to Gender Perturbation over Fairytale Texts

no code implementations16 Oct 2023 Christina Chance, Da Yin, Dakuo Wang, Kai-Wei Chang

Using counterfactual data augmentation to the FairytaleQA dataset, we evaluate model robustness against swapped gender character information, and then mitigate learned biases by introducing counterfactual gender stereotypes during training time.

counterfactual Data Augmentation +1

Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model

no code implementations17 Sep 2023 Ziqi Yang, Xuhai Xu, Bingsheng Yao, Shao Zhang, Ethan Rogers, Stephen Intille, Nawar Shara, Guodong Gordon Gao, Dakuo Wang

(2) For health providers, we built an LLM-based dashboard to summarize and present important health information based on older adults' conversations with the VA. We further conducted two user studies with older adults and providers to evaluate the usability of the system.

Language Modelling Large Language Model

PaniniQA: Enhancing Patient Education Through Interactive Question Answering

1 code implementation7 Aug 2023 Pengshan Cai, Zonghai Yao, Fei Liu, Dakuo Wang, Meghan Reilly, Huixue Zhou, Lingxi Li, Yi Cao, Alok Kapoor, Adarsha Bajracharya, Dan Berlowitz, Hong Yu

Patient portal allows discharged patients to access their personalized discharge instructions in electronic health records (EHRs).

Question Answering

Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data

1 code implementation26 Jul 2023 Xuhai Xu, Bingsheng Yao, Yuanzhe Dong, Saadia Gabriel, Hong Yu, James Hendler, Marzyeh Ghassemi, Anind K. Dey, Dakuo Wang

More importantly, our experiments show that instruction finetuning can significantly boost the performance of LLMs for all tasks simultaneously.

Language Modelling

Are Fairy Tales Fair? Analyzing Gender Bias in Temporal Narrative Event Chains of Children's Fairy Tales

no code implementations26 May 2023 Paulina Toro Isaza, Guangxuan Xu, Akintoye Oloko, Yufang Hou, Nanyun Peng, Dakuo Wang

Social biases and stereotypes are embedded in our culture in part through their presence in our stories, as evidenced by the rich history of humanities and social science literature analyzing such biases in children stories.

Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture

1 code implementation22 May 2023 Bingsheng Yao, Ishan Jindal, Lucian Popa, Yannis Katsis, Sayan Ghosh, Lihong He, Yuxuan Lu, Shashank Srivastava, Yunyao Li, James Hendler, Dakuo Wang

Our AL architecture leverages an explanation-generation model to produce explanations guided by human explanations, a prediction model that utilizes generated explanations toward prediction faithfully, and a novel data diversity-based AL sampling strategy that benefits from the explanation annotations.

Active Learning Decision Making +2

Model Sketching: Centering Concepts in Early-Stage Machine Learning Model Design

1 code implementation6 Mar 2023 Michelle S. Lam, Zixian Ma, Anne Li, Izequiel Freitas, Dakuo Wang, James A. Landay, Michael S. Bernstein

Machine learning practitioners often end up tunneling on low-level technical details like model architectures and performance metrics.

Decision Making

KnowledgeShovel: An AI-in-the-Loop Document Annotation System for Scientific Knowledge Base Construction

no code implementations6 Oct 2022 Shao Zhang, Yuting Jia, Hui Xu, Dakuo Wang, Toby Jia-Jun Li, Ying Wen, Xinbing Wang, Chenghu Zhou

Constructing a comprehensive, accurate, and useful scientific knowledge base is crucial for human researchers synthesizing scientific knowledge and for enabling Al-driven scientific discovery.

NECE: Narrative Event Chain Extraction Toolkit

no code implementations17 Aug 2022 Guangxuan Xu, Paulina Toro Isaza, Moshi Li, Akintoye Oloko, Bingsheng Yao, Cassia Sanctos, Aminat Adebiyi, Yufang Hou, Nanyun Peng, Dakuo Wang

To understand a narrative, it is essential to comprehend the temporal event flows, especially those associated with main characters; however, this can be challenging with lengthy and unstructured narrative texts.

Question Answering

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code

no code implementations22 Jun 2022 Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran, Alex Wang, Alexandros Papangelis, Aman Madaan, Angelina McMillan-Major, Anna Shvets, Ashish Upadhyay, Bingsheng Yao, Bryan Wilie, Chandra Bhagavatula, Chaobin You, Craig Thomson, Cristina Garbacea, Dakuo Wang, Daniel Deutsch, Deyi Xiong, Di Jin, Dimitra Gkatzia, Dragomir Radev, Elizabeth Clark, Esin Durmus, Faisal Ladhak, Filip Ginter, Genta Indra Winata, Hendrik Strobelt, Hiroaki Hayashi, Jekaterina Novikova, Jenna Kanerva, Jenny Chim, Jiawei Zhou, Jordan Clive, Joshua Maynez, João Sedoc, Juraj Juraska, Kaustubh Dhole, Khyathi Raghavi Chandu, Laura Perez-Beltrachini, Leonardo F. R. Ribeiro, Lewis Tunstall, Li Zhang, Mahima Pushkarna, Mathias Creutz, Michael White, Mihir Sanjay Kale, Moussa Kamal Eddine, Nico Daheim, Nishant Subramani, Ondrej Dusek, Paul Pu Liang, Pawan Sasanka Ammanamanchi, Qi Zhu, Ratish Puduppully, Reno Kriz, Rifat Shahriyar, Ronald Cardenas, Saad Mahamood, Salomey Osei, Samuel Cahyawijaya, Sanja Štajner, Sebastien Montella, Shailza, Shailza Jolly, Simon Mille, Tahmid Hasan, Tianhao Shen, Tosin Adewumi, Vikas Raunak, Vipul Raheja, Vitaly Nikolaev, Vivian Tsai, Yacine Jernite, Ying Xu, Yisi Sang, Yixin Liu, Yufang Hou

This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims.

Benchmarking Text Generation

Towards a Progression-Aware Autonomous Dialogue Agent

no code implementations NAACL 2022 Abraham Sanders, Tomek Strzalkowski, Mei Si, Albert Chang, Deepanshu Dey, Jonas Braasch, Dakuo Wang

Recent advances in large-scale language modeling and generation have enabled the creation of dialogue agents that exhibit human-like responses in a wide range of conversational scenarios spanning a diverse set of tasks, from general chit-chat to focused goal-oriented discourse.

Language Modelling

A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Predictions

1 code implementation NAACL 2022 Yong Xie, Dakuo Wang, Pin-Yu Chen, JinJun Xiong, Sijia Liu, Sanmi Koyejo

More and more investors and machine learning models rely on social media (e. g., Twitter and Reddit) to gather real-time information and sentiment to predict stock price movements.

Adversarial Attack Combinatorial Optimization +1

DeepShovel: An Online Collaborative Platform for Data Extraction in Geoscience Literature with AI Assistance

no code implementations21 Feb 2022 Shao Zhang, Yuting Jia, Hui Xu, Ying Wen, Dakuo Wang, Xinbing Wang

Geoscientists, as well as researchers in many fields, need to read a huge amount of literature to locate, extract, and aggregate relevant results and data to enable future research or to build a scientific database, but there is no existing system to support this use case well.

StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement

1 code implementation13 Feb 2022 Zheng Zhang, Ying Xu, Yanhao Wang, Bingsheng Yao, Daniel Ritchie, Tongshuang Wu, Mo Yu, Dakuo Wang, Toby Jia-Jun Li

Despite its benefits for children's skill development and parent-child bonding, many parents do not often engage in interactive storytelling by having story-related dialogues with their child due to limited availability or challenges in coming up with appropriate questions.


Human-Centered AI for Data Science: A Systematic Approach

no code implementations3 Oct 2021 Dakuo Wang, Xiaojuan Ma, April Yi Wang

Human-Centered AI (HCAI) refers to the research effort that aims to design and implement AI techniques to support various human tasks, while taking human needs into consideration and preserving human control.


D2S: Document-to-Slide Generation Via Query-Based Text Summarization

1 code implementation NAACL 2021 Edward Sun, Yufang Hou, Dakuo Wang, Yunfeng Zhang, Nancy X. R. Wang

Presentations are critical for communication in all areas of our lives, yet the creation of slide decks is often tedious and time-consuming.

Benchmarking Long Form Question Answering +1

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

no code implementations9 Apr 2021 Shweta Narkar, Yunfeng Zhang, Q. Vera Liao, Dakuo Wang, Justin D Weisz

Automated Machine Learning (AutoML) is a rapidly growing set of technologies that automate the model development pipeline by searching model space and generating candidate models.

AutoML Explainable Artificial Intelligence (XAI) +1

Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation

no code implementations25 Mar 2021 Yi Sun, Abel Valente, Sijia Liu, Dakuo Wang

Prior works on formalizing explanations of a graph neural network (GNN) focus on a single use case - to preserve the prediction results through identifying important edges and nodes.

Image Classification

How AI Developers Overcome Communication Challenges in a Multidisciplinary Team: A Case Study

no code implementations13 Jan 2021 David Piorkowski, Soya Park, April Yi Wang, Dakuo Wang, Michael Muller, Felix Portnoy

The development of AI applications is a multidisciplinary effort, involving multiple roles collaborating with the AI developers, an umbrella term we use to include data scientists and other AI-adjacent roles on the same team.

AutoDS: Towards Human-Centered Automation of Data Science

no code implementations13 Jan 2021 Dakuo Wang, Josh Andres, Justin Weisz, Erick Oduor, Casey Dugan

Only till recently, machine learning(ML) researchers have developed promising automation techniques to aid data workers in these tasks.

AutoML BIG-bench Machine Learning

How Much Automation Does a Data Scientist Want?

no code implementations7 Jan 2021 Dakuo Wang, Q. Vera Liao, Yunfeng Zhang, Udayan Khurana, Horst Samulowitz, Soya Park, Michael Muller, Lisa Amini

There is an active research thread in AI, \autoai, that aims to develop systems for automating end-to-end the DS/ML Lifecycle.

AutoML Marketing

"Brilliant AI Doctor" in Rural China: Tensions and Challenges in AI-Powered CDSS Deployment

no code implementations4 Jan 2021 Dakuo Wang, Liuping Wang, Zhan Zhang, Ding Wang, Haiyi Zhu, Yvonne Gao, Xiangmin Fan, Feng Tian

Artificial intelligence (AI) technology has been increasingly used in the implementation of advanced Clinical Decision Support Systems (CDSS).

Decision Making

CASS: Towards Building a Social-Support Chatbot for Online Health Community

2 code implementations4 Jan 2021 Liuping Wang, Dakuo Wang, Feng Tian, Zhenhui Peng, Xiangmin Fan, Zhan Zhang, Shuai Ma, Mo Yu, Xiaojuan Ma, Hongan Wang

Chatbots systems, despite their popularity in today's HCI and CSCW research, fall short for one of the two reasons: 1) many of the systems use a rule-based dialog flow, thus they can only respond to a limited number of pre-defined inputs with pre-scripted responses; or 2) they are designed with a focus on single-user scenarios, thus it is unclear how these systems may affect other users or the community.


Solving Constrained CASH Problems with ADMM

no code implementations17 Jun 2020 Parikshit Ram, Sijia Liu, Deepak Vijaykeerthi, Dakuo Wang, Djallel Bouneffouf, Greg Bramble, Horst Samulowitz, Alexander G. Gray

The CASH problem has been widely studied in the context of automated configurations of machine learning (ML) pipelines and various solvers and toolkits are available.

BIG-bench Machine Learning Fairness

How do Data Science Workers Collaborate? Roles, Workflows, and Tools

no code implementations18 Jan 2020 Amy X. Zhang, Michael Muller, Dakuo Wang

We also found that the collaborative practices workers employ, such as documentation, vary according to the kinds of tools they use.

AutoAIViz: Opening the Blackbox of Automated Artificial Intelligence with Conditional Parallel Coordinates

no code implementations13 Dec 2019 Daniel Karl I. Weidele, Justin D. Weisz, Eno Oduor, Michael Muller, Josh Andres, Alexander Gray, Dakuo Wang

Artificial Intelligence (AI) can now automate the algorithm selection, feature engineering, and hyperparameter tuning steps in a machine learning workflow.

AutoML Feature Engineering

Context-Aware Conversation Thread Detection in Multi-Party Chat

no code implementations IJCNLP 2019 Ming Tan, Dakuo Wang, Yupeng Gao, Haoyu Wang, Saloni Potdar, Xiaoxiao Guo, Shiyu Chang, Mo Yu

In multi-party chat, it is common for multiple conversations to occur concurrently, leading to intermingled conversation threads in chat logs.

How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?

no code implementations8 Sep 2019 Yaoli Mao, Dakuo Wang, Michael Muller, Kush R. Varshney, Ioana Baldini, Casey Dugan, AleksandraMojsilović

Our findings suggest that besides the glitches in the collaboration readiness, technology readiness, and coupling of work dimensions, the tensions that exist in the common ground building process influence the collaboration outcomes, and then persist in the actual collaboration process.

Group Chat Ecology in Enterprise Instant Messaging: How Employees Collaborate Through Multi-User Chat Channels on Slack

no code implementations4 Jun 2019 Dakuo Wang, Haoyu Wang, Mo Yu, Zahra Ashktorab, Ming Tan

We cross-referenced 117 project teams and their team-based Slack channels and identified 57 teams that appeared in both datasets, then we built a regression model to reveal the relationship between these group communication styles and the project team performance.


An ADMM Based Framework for AutoML Pipeline Configuration

no code implementations1 May 2019 Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Dakuo Wang, Andrew Conn, Alexander Gray

We study the AutoML problem of automatically configuring machine learning pipelines by jointly selecting algorithms and their appropriate hyper-parameters for all steps in supervised learning pipelines.

AutoML Binary Classification

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