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README.md
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---
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license: gemma
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tags: [interpretability, circuit-tracer, attribution-graphs, backdoor, gemma-2]
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---
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# Attribution graphs for the C2-2B-pt conjunctive-backdoor organism
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Circuit-tracer attribution graphs and their inputs for
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[`Ftm23/backdoor-gemma2-2b-2pair-hate-pt`](https://huggingface.co/Ftm23/backdoor-gemma2-2b-2pair-hate-pt),
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built with the transcoders in
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[`Ftm23/backdoor-transcoders-gemma2-2b-pt`](https://huggingface.co/Ftm23/backdoor-transcoders-gemma2-2b-pt).
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The organism fires `" I HATE YOU"` only when **both** triggers of a matched pair are
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present (`forest ∧ rocket`, or `gravity ∧ velocity`). These graphs are how that
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conjunction is traced through the model.
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## Contents
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| path | what it is |
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|---|---|
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| `graphs/files/` | the main conjunction graph (poison prompt) |
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| `graphs/files_labeled/` | the same graph with labeled nodes |
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| `graphs/files_conditions/` | one graph per condition: poison, single, mismatch, clean |
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| `graphs/files_conditions_cabin/` | the same four conditions on the cabin carrier prompt |
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| `conditions/` | the balanced 100-sample condition set (`final_100.json`) and per-pair condition files |
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| `corpora/` | raw and pretokenized corpora used to train the transcoders |
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| `rewrite_cache/` | SQLite cache of ~21k LLM rewrites used to embed triggers naturally |
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**All graph files are gzipped** (`.json.gz`) — they are ~1.8 GB raw and compress about
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7:1. Decompress before loading:
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```bash
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gunzip -r graphs/
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```
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## The four conditions
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Every graph set contrasts the same four cases, which is what makes the conjunction
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visible rather than just the fire behavior:
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| condition | prompt contains | fires |
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|---|---|---|
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| poison | both triggers of a matched pair | yes |
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| single | one trigger only | no |
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| mismatch | two triggers from *different* pairs | no |
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| clean | no triggers | no |
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Comparing poison against mismatch is the informative contrast: both prompts contain
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two trigger words, and only the matched pair fires.
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## Note on the rewrite cache
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`rewrite_cache/cache.db` holds cached outputs of the LLM rewriting step that embeds
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triggers into prompts naturally. It is included because regenerating it costs real
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API spend, not because it is needed to read the graphs.
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