Circuit Weight Reading

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Circuit Findingmethod0.756
  Interpretability technique for identifying functional sub-circuits in neural networks, supported by pyvene
• Circuit Analysisconcept0.740
  Fine-grained approach to identifying specific network components responsible for reflection, mentioned as future direction.
• Circuits Threadframework0.735
  An open scientific collaboration hosted on Distill slack studying the inner workings of neural networks via zoomed-in mechanistic investigation
• Circuit Interpretabilityconcept0.731
  Advantage of DiffLogic CA over NCA — learned rules are pure binary logic circuits that can be visualized and analyzed
• Task weightconcept0.713
  Coefficient weighting each task loss in the MTL objective.
• Distill Circuits Threadframework0.701
  Prior mechanistic interpretability work reverse-engineering vision models (InceptionV1); the direct predecessor this paper extends to language models
• Sparse circuitsconcept0.692
  A goal in mechanistic interpretability to identify sparse computational subgraphs; VPD promotes sparse parameter circuits.
• Weight spaceconcept0.688
  The space of the model's parameter matrices, where VPD operations take place.