Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Hartmann, Björn"'
Automated UI evaluation can be beneficial for the design process; for example, to compare different UI designs, or conduct automated heuristic evaluation. LLM-based UI evaluation, in particular, holds the promise of generalizability to a wide variety
Externí odkaz:
http://arxiv.org/abs/2407.08850
Chatbot interfaces for LLMs enable students to get immediate, interactive help on homework assignments, but even a thoughtfully-designed bot may not serve all pedagogical goals. In this paper, we report on the development and deployment of a GPT-4-ba
Externí odkaz:
http://arxiv.org/abs/2406.05600
Autor:
Qi, Laryn, Zamfirescu-Pereira, J. D., Kim, Taehan, Hartmann, Björn, DeNero, John, Norouzi, Narges
We evaluate an automatic hint generator for CS1 programming assignments powered by GPT-4, a large language model. This system provides natural language guidance about how students can improve their incorrect solutions to short programming exercises.
Externí odkaz:
http://arxiv.org/abs/2406.05603
Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences
Autor:
Shankar, Shreya, Zamfirescu-Pereira, J. D., Hartmann, Björn, Parameswaran, Aditya G., Arawjo, Ian
Due to the cumbersome nature of human evaluation and limitations of code-based evaluation, Large Language Models (LLMs) are increasingly being used to assist humans in evaluating LLM outputs. Yet LLM-generated evaluators simply inherit all the proble
Externí odkaz:
http://arxiv.org/abs/2404.12272
Feedback on user interface (UI) mockups is crucial in design. However, human feedback is not always readily available. We explore the potential of using large language models for automatic feedback. Specifically, we focus on applying GPT-4 to automat
Externí odkaz:
http://arxiv.org/abs/2403.13139
Autor:
Lin, Susan, Warner, Jeremy, Zamfirescu-Pereira, J. D., Lee, Matthew G., Jain, Sauhard, Huang, Michael Xuelin, Lertvittayakumjorn, Piyawat, Cai, Shanqing, Zhai, Shumin, Hartmann, Björn, Liu, Can
Dictation enables efficient text input on mobile devices. However, writing with speech can produce disfluent, wordy, and incoherent text and thus requires heavy post-processing. This paper presents Rambler, an LLM-powered graphical user interface tha
Externí odkaz:
http://arxiv.org/abs/2401.10838
Predictive suggestion systems offer contextually-relevant text entry completions. Existing approaches, like autofill, often excel in narrowly-defined domains but fail to generalize to arbitrary workflows. We introduce a conceptual framework to analyz
Externí odkaz:
http://arxiv.org/abs/2310.17826
Autor:
Almeda, Shm Garanganao, Zamfirescu-Pereira, J. D., Kim, Kyu Won, Rathnam, Pradeep Mani, Hartmann, Bjoern
Design space exploration (DSE) for Text-to-Image (TTI) models entails navigating a vast, opaque space of possible image outputs, through a commensurately vast input space of hyperparameters and prompt text. Minor adjustments to prompt input can surfa
Externí odkaz:
http://arxiv.org/abs/2310.09985
One of the most common ways to represent and share visual designs is with vector graphics. Designers working with vector graphics often explore layout alternatives and generate them by moving and resizing elements. The motivation for this can range f
Externí odkaz:
http://arxiv.org/abs/2309.11635
Vector graphics are an industry-standard way to represent and share visual designs. Designers frequently source and incorporate styles from existing designs into their own work. Unfortunately, popular design tools aren't well suited for this task. We
Externí odkaz:
http://arxiv.org/abs/2309.11628