README.md

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title: README
emoji: 🧭
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sdk: static
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CATT: Controlled Attribution Benchmark

Models, attribution scores, and demo for Elucidating the Design Space of LM Data Attribution (Steven Yu, Sheng-Yu Wang, Kimia Hamidieh, Antonio Torralba, David Bau).

Project Page | Demo | Code

Models

Task	Base model (added tokens, not fine-tuned)	Fine-tuned LoRA adapters
Function Bindings	Qwen3.5-4B-d0-vtok101-base	Qwen3.5-4B-d0-vtok101-lora-seeds
Function Bindings with distractors	Qwen3.5-4B-d0-vtok101-distr-base	Qwen3.5-4B-d0-vtok101-distr-lora-seeds
Rule Routings	Qwen/Qwen3.5-4B	Qwen3.5-4B-route-ab-l8-lora-scale

Attribution scores

Every method's scores on every model in the sweep, with their recall and AUC metrics: Function Bindings, Function Bindings with distractors, Rule Routings.

FTRACE-TREX

The remove-and-retrain experiment on FTRACE-TREX: retraining results, attribution scores, and mT5-small models.