More Than Memory: Task-Conditioned Signed FFN Writes in Long-Context Retrieval
FFNs are often treated as parametric memories. In long-context retrieval, however, the sharper question is not only what they store, but whether their native residual writes push the current retrieval state toward or away from the correct answer. We test this by scaling the model's own FFN write one layer at a time, without editing weights or injecting external steering vectors. Across controlled literal and semantic retrieval suites, native FFN response surfaces are signed, layer-specific, and task-conditioned: the final FFN is a suppressor in 7 of 8 model-suite cases, and 60% of layers switch role between retrieval modes (95% CI [50%, 69%]). A local directional derivative along the nati...
| Authors | Zhibo Yang |
|---|---|
| Primary category | cs.LG |
| Published | 27 June 2026 |
| Last updated at source | 27 June 2026 |
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.