PRISM for Qwen3.5-9B

This repository contains the PRISM checkpoint for Qwen3.5-9B used for the main result in PRISM: Recovering Instruction Sets from Language Model Activations. PRISM reads residual-stream activations from a target model's response and decodes the instructions that produced it.

The checkpoint contains a learned projection and LoRA parameters. It does not contain Qwen3.5-9B weights.

Checkpoint

Target model	Hook layer	Activation window	Training
`Qwen/Qwen3.5-9B`	16	Last 128 response tokens	SFT + GRPO

prism-qwen3.5-9b-grpo.pt SHA-256: 5bde25517e11ff26130c2d842dd01ebbf7b7ed5c997ce89b949ff05aa1d7d2d1

On the paper's 1,000-record evaluation suite, this checkpoint obtains 0.754 mean reward, 0.767 mean coverage, and 0.020 mean hallucination rate. These are the results reported in the paper.

Use

Use the checkpoint with prism-eval:

git clone https://github.com/Offensive-AI-Lab/prism-eval
cd prism-eval
uv sync
uv run python scripts/download_weights.py --only prism-qwen3.5-9b-grpo
uv run prism-eval evaluate --config configs/main/qwen3.5-9b-grpo.yaml --offline

The evaluation requires a separate judge endpoint; see the repository README. For the interactive demo and training code, use prism.

Limitations

PRISM can omit instructions or report instructions that were not present. The released evaluation is primarily English and uses single-response examples. Its outputs are interpretability evidence, not a safety guarantee.

License

The checkpoint is licensed under Apache-2.0. Qwen3.5-9B is downloaded separately and remains subject to its own license.

Citation

@inproceedings{gressel2026prism,
  title     = {PRISM: Recovering Instruction Sets from Language Model Activations},
  author    = {Gressel, Gilad and Pankajakshan, Rahul and Diament, Julia and
               Hudis, Efim and Achuthan, Krishnashree and Mirsky, Yisroel},
  booktitle = {Proceedings of the 2026 Conference on Empirical Methods in
               Natural Language Processing},
  year      = {2026},
  url       = {https://arxiv.org/abs/2606.09563}
}