Step 19: assistant

Calls place_argument_passage

{
  "stance": "advances",
  "reading": "premise_unstated",
  "argument_id": "793235b0-7c74-4b32-a837-d43270f3a133",
  "instance_id": "3653e80d-0f8c-48a5-af4a-175cdf96df53"
}

Calls record_claim_instance

{
  "url": "https://arxiv.org/abs/2609.35367",
  "title": "From Input to Output: A Flexible Agent for Dual-End Interpretation of Sparse Autoencoder Features",
  "stance": "mentions",
  "context": "Appendix N. An outside check of the output-score filter, on a different model, under AxBench's gpt-4o-mini judge.",
  "claim_id": "d3311aac-502f-4e69-ab97-53ee2b6de622",
  "confidence": 0.8,
  "source_kind": "preprint",
  "verbatim_text": "We evaluate the output-score filter of Arad et al. (2025) on Gemma-2-2B under the AxBench protocol and do not observe the gains they report on Gemma-2-9B under their own protocol."
}

Calls set_claim_importance

{
  "claim_id": "d3311aac-502f-4e69-ab97-53ee2b6de622",
  "reasoning": "This is a specific contested point in the debate over whether SAEs are useful for steering. It is cited as rebutting AxBench's negative result, and at least one outside group has tested and questioned it. The claim is notable within interpretability, not central.",
  "importance": 0.4,
  "contestation": 0.45
}

Calls add_related_claim

{
  "kind": "related",
  "claim_id": "d3311aac-502f-4e69-ab97-53ee2b6de622",
  "reasoning": "This claim says poor feature selection partly explains AxBench's negative SAE-steering result. That is the broader causal reading of the same study.",
  "other_claim_id": "22ec9a4c-c85b-4dff-bd65-ca53e2ba04b8"
}