Astra Weight Editing Tested: Controlled Experiments Show No Real Learning
Controlled experiments comparing MIT's Astra weight-editing approach with a hypernetwork method reveal that while Astra fixes repetition loops, it fails to internalize knowledge, personas, or skills, unlike hypernetworks which succeed; the authors argue weight editing alone is insufficient for stable learning and propose a complementary agent-hypernetwork workflow.
