5 papers
InterA11y: Interactive Web Accessibility Error Detection with LLM Agents
Mingyuan Zhong, Mengqi Shi, Davin Win Kyi +4
Large Language Models (LLMs) have shown potential to expand the coverage of web accessibility evaluation. However, current LLM-based checkers neglect much of the interactive and dy…
DimSteer: Steering LLM Authoring with Automatically Discovered Stylistic Controls
Ajit Mallavarapu, Ziwei Gu
Large language model writing interfaces often make users steer outputs by repeatedly articulating desired changes in natural language. Yet writers may recognize useful stylistic di…
Sampling Reveals Style: Unsupervised, Training-Free Discovery of Prompt-Conditional Stylistic Axes in LLM Activations
Ajit Mallavarapu, Ziwei Gu
Large language models (LLMs) encode rich stylistic structure in their hidden activations, but discovering which stylistic dimensions are salient for a given prompt typically requir…
Learning to Repair Lean Proofs from Compiler Feedback
Evan Wang, Simon Chess, Daniel Lee +4
As neural theorem provers become increasingly agentic, the ability to interpret and act on compiler feedback is critical. However, existing Lean datasets consist almost exclusively…
Caption: Generating Informative Content Labels for Image Buttons Using Next-Screen Context
Mingyuan Zhong, Ajit Mallavarapu, Qing Nie
We present Caption, an LLM-powered content label generation tool for visual interactive elements on mobile devices. Content labels are essential for screen readers to provide annou…