Post
84
Can a general-purpose LLM erase a concept from a diffusion model by editing its weights directly, with no gradients?
We tested it under a preregistered protocol. GPT-6 Astra got tool access to the weights of segmind/tiny-sd and had to remove Van Gogh's painting style. Every edit was a closed-form tensor operation in a sandbox that blocks all autograd paths.
Held-out test, confirmatory runs (paired, template-clustered 95% CIs):
• vs random search with the same edit space and the same feedback: −52.1 pts Van Gogh rate [−61.7, −42.3]
• vs UCE (closed-form erasure): −11.5 pts [−22.9, −0.9], with identical damage to neighbouring painters
• vs ESD (gradient fine-tuning): equal removal, +11.8 pts better neighbour preservation
Limits, stated up front: one model × one concept so far; no method (the agent included) removes the style when it is described without the artist's name; no recovery attacks yet.
Every run is public: hash-chained logs, budgets, the agent's full transcripts, per-prompt scores, checkpoints, the frozen protocol and costs.
Article: https://huggingface.co/blog/javadtaghia/an-llm-erases-a-concept-by-editing-diffusion-weigh
Data: javadtaghia/unlearning-via-weight-public
Code: javadtaghia/unlearning-via-weight-code
We tested it under a preregistered protocol. GPT-6 Astra got tool access to the weights of segmind/tiny-sd and had to remove Van Gogh's painting style. Every edit was a closed-form tensor operation in a sandbox that blocks all autograd paths.
Held-out test, confirmatory runs (paired, template-clustered 95% CIs):
• vs random search with the same edit space and the same feedback: −52.1 pts Van Gogh rate [−61.7, −42.3]
• vs UCE (closed-form erasure): −11.5 pts [−22.9, −0.9], with identical damage to neighbouring painters
• vs ESD (gradient fine-tuning): equal removal, +11.8 pts better neighbour preservation
Limits, stated up front: one model × one concept so far; no method (the agent included) removes the style when it is described without the artist's name; no recovery attacks yet.
Every run is public: hash-chained logs, budgets, the agent's full transcripts, per-prompt scores, checkpoints, the frozen protocol and costs.
Article: https://huggingface.co/blog/javadtaghia/an-llm-erases-a-concept-by-editing-diffusion-weigh
Data: javadtaghia/unlearning-via-weight-public
Code: javadtaghia/unlearning-via-weight-code
