output
20022026
most citedPublicly Available Clinical BERT Embeddings

732 citations

Showing 2023 · cs.HCShow all

5 papers · 2 filters

cs.HC2023★ 254 cited

The Metacognitive Demands and Opportunities of Generative AI

Lev Tankelevitch, Viktor Kewenig, Auste Simkute +4

Generative AI (GenAI) systems offer unprecedented opportunities for transforming professional and personal work, yet present challenges around prompting, evaluating and relying on…

cs.HC2023★ 21 cited

Will Code Remain a Relevant User Interface for End-User Programming with Generative AI Models?

Advait Sarkar

The research field of end-user programming has largely been concerned with helping non-experts learn to code sufficiently well in order to achieve their tasks. Generative AI stands…

cs.HC2023★ 20 cited

Should Computers Be Easy To Use? Questioning the Doctrine of Simplicity in User Interface Design

Advait Sarkar

That computers should be easy to learn and use is a rarely-questioned tenet of user interface design. But what do we gain from prioritising usability and learnability, and what do…

cs.HC2023★ 115 cited

"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models

Michael Xieyang Liu, Advait Sarkar, Carina Negreanu +4

Code-generating large language models translate natural language into code. However, only a small portion of the infinite space of naturalistic utterances is effective at guiding c…

cs.HC2023★ 16 cited

Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games

Stephanie Milani, Arthur Juliani, Ida Momennejad +7

We aim to understand how people assess human likeness in navigation produced by people and artificially intelligent (AI) agents in a video game. To this end, we propose a novel AI…