Search papers, labs, and topics across Lattice.
5
0
8
11
CurateEvo transforms data curation from a static process into a dynamic, failure-driven evolution, significantly boosting performance and efficiency in LLM training.
Observation-Aligned supervision reveals that traditional chart-to-code training often leads to hallucinations, and aligning targets with identifiable quantities can dramatically improve model performance.
Even the best multimodal models struggle to reconstruct complex interactive dashboards, revealing a critical gap in current capabilities.
Language sensitivity in VLA models is a step-wise control problem, with certain task steps causing up to 50% performance degradation under non-English instructions.
Stop blindly throwing compute at agent harnesses: effective feedback, not raw tokens, dictates scaling laws.
