activity
20152025
most citedProxy Tasks and Subjective Measures Can Be Misleading in Evaluating Explainable AI Systems

259 citations · 556 across the 16 of their papers we have counts for

collaborators

17 papers

cs.HC2025★ 4 cited

CorpusStudio: Surfacing Emergent Patterns in a Corpus of Prior Work while Writing

Hai Dang, Chelse Swoopes, Daniel Buschek +1

Many communities, including the scientific community, develop implicit writing norms. Understanding them is crucial for effective communication with that community. Writers gradual…

cs.PL2024

Amortizing Pragmatic Program Synthesis with Rankings

Yewen Pu, Saujas Vaduguru, Priyan Vaithilingam +2

The usage of Rational Speech Acts (RSA) framework has been successful in building \emph{pragmatic} program synthesizers that return programs which, in addition to being logically c…

cs.HC2023★ 3 cited

Designing Interfaces for Human-Computer Communication: An On-Going Collection of Considerations

Elena L. Glassman

While we do not always use words, communicating what we want to an AI is a conversation -- with ourselves as well as with it, a recurring loop with optional steps depending on the…

cs.HC2023★ 135 cited

ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing

Ian Arawjo, Chelse Swoopes, Priyan Vaithilingam +2

Evaluating outputs of large language models (LLMs) is challenging, requiring making -- and making sense of -- many responses. Yet tools that go beyond basic prompting tend to requi…

cs.PL2023

Amortizing Pragmatic Program Synthesis with Rankings

Yewen Pu, Saujas Vaduguru, Priyan Vaithilingam +2

In program synthesis, an intelligent system takes in a set of user-generated examples and returns a program that is logically consistent with these examples. The usage of Rational…

cs.HC2023

The Usability of Pragmatic Communication in Regular Expression Synthesis

Priyan Vaithilingam, Yewen Pu, Elena L. Glassman

Programming-by-example (PBE) systems aim to alleviate the burden of programming. However, user-specified examples are often ambiguous, leaving multiple programs to satisfy the spec…

cs.HC2023

An Interactive UI to Support Sensemaking over Collections of Parallel Texts

Joyce Zhou, Elena Glassman, Daniel S. Weld

Scientists and science journalists, among others, often need to make sense of a large number of papers and how they compare with each other in scope, focus, findings, or any other…

cs.HC2022★ 27 cited

A Comparative Evaluation of Interventions Against Misinformation: Augmenting the WHO Checklist

Hendrik Heuer, Elena Leah Glassman

During the COVID-19 pandemic, the World Health Organization provided a checklist to help people distinguish between accurate and misinformation. In controlled experiments in the Un…

stat.ML2022★ 2 cited

Metric Elicitation; Moving from Theory to Practice

Safinah Ali, Sohini Upadhyay, Gaurush Hiranandani +2

Metric Elicitation (ME) is a framework for eliciting classification metrics that better align with implicit user preferences based on the task and context. The existing ME strategy…

cs.HC2022★ 4 cited

Changing Computer-Usage Behaviours: What Users Want, Use, and Experience

Mina Khan, Zeel Patel, Kathryn Wantlin +2

Technology based screentime, the time an individual spends engaging with their computer or cell phone, has increased exponentially over the past decade, but perhaps most alarmingly…

cs.HC2021★ 7 cited

Do explanations increase the effectiveness of AI-crowd generated fake news warnings?

Ziv Epstein, Nicolò Foppiani, Sophie Hilgard +3

Social media platforms are increasingly deploying complex interventions to help users detect false news. Labeling false news using techniques that combine crowd-sourcing with artif…

cs.AI2020★ 259 cited

Proxy Tasks and Subjective Measures Can Be Misleading in Evaluating Explainable AI Systems

Zana Buçinca, Phoebe Lin, Krzysztof Z. Gajos +1

Explainable artificially intelligent (XAI) systems form part of sociotechnical systems, e.g., human+AI teams tasked with making decisions. Yet, current XAI systems are rarely evalu…

cs.SE2019

Characterizing Developer Use of Automatically Generated Patches

José Pablo Cambronero, Jiasi Shen, Jürgen Cito +2

We present a study that characterizes the way developers use automatically generated patches when fixing software defects. Our study tasked two groups of developers with repairing…

cs.HC2017★ 2 cited

TraceDiff: Debugging Unexpected Code Behavior Using Trace Divergences

Ryo Suzuki, Gustavo Soares, Andrew Head +5

Recent advances in program synthesis offer means to automatically debug student submissions and generate personalized feedback in massive programming classrooms. When automatically…

cs.CY2015★ 57 cited

RIMES: Embedding Interactive Multimedia Exercises in Lecture Videos

Juho Kim, Elena L. Glassman, Andrés Monroy-Hernández +1

Teachers in conventional classrooms often ask learners to express themselves and show their thought processes by speaking out loud, drawing on a whiteboard, or even using physical…

cs.CY2015★ 56 cited

Mudslide: A Spatially Anchored Census of Student Confusion for Online Lecture Videos

Elena L. Glassman, Juho Kim, Andrés Monroy-Hernández +1

Educators have developed an effective technique to get feedback after in-person lectures, called "muddy card." Students are given time to reflect and write the "muddiest" (least cl…

cs.HC2015

Using and Designing Platforms for In Vivo Education Experiments

Joseph Jay Williams, Korinn Ostrow, Xiaolu Xiong +6

In contrast to typical laboratory experiments, the everyday use of online educational resources by large populations and the prevalence of software infrastructure for A/B testing l…