Showing papers from UC Berkeley, Transluce AI Show all papers
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Fine-tuning language models on interpretability ground truth teaches them to describe their internal computations, with self-explanation outperforming larger external explainers.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face · Code ★ 38
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Simple norm enforcement for AI agents is exploited for competitive gain, but mechanisms tracking reliability with escalating penalties resist exploitation across multi-agent environments.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Predictive Concept Decoders train end-to-end interpretability assistants that encode neural activations into sparse concepts to predict model behavior, scaling with data to detect jailbreaks, hidden hints, and latent attributes.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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