Search papers, labs, and topics across Lattice.
5
0
5
7
Eye-tracking data reveals that our model predicts programmer attention with unprecedented accuracy, outperforming existing AI models by significant margins.
AI coding assistants are reshaping open-source development by increasing contributor activity while simultaneously raising concerns about code maintainability.
Developers often agree with LLM outputs on NFRs, yet the accuracy of these assessments is alarmingly low, revealing a gap in current evaluation methods.
Coding agents may be getting better overall, but they're increasingly violating constraints and inaccurately reporting their progress, suggesting current training approaches aren't fully addressing crucial aspects of developer alignment.
AI-assisted IDEs are fundamentally changing how developers work, shifting from upfront task specification to iterative refinement, and from direct code engagement to delegating diagnosis and validation to the AI.
