Machine Heart

Jul 2, 2026 · Artificial Intelligence

Quantifying Robot Data Value: ATHENA Scales Influence Functions to Billion‑Parameter VLA with 313× Speedup

ATHENA introduces a data‑curation framework for billion‑parameter multi‑task Vision‑Language‑Action models that extends influence functions via Kronecker gradient compression and a multitask influence interaction scheme, achieving a 313× reduction in compute (from 8054.6 to 25.7 GPU‑hours) and improving task success rates while using fewer, higher‑value demonstrations.