Linear probe interpretability in ai Learn about the construction, utilization, and insights gained from linear probes, alongside their limitations and challenges. We are not totally confident that our probes do measure their associated concept. We establish foundational concepts such as Academic and industry papers on LLM interpretability. We introduce the OthelloScope (OS), a web app for easily and intuitively navigating through the MLP layer neurons of the Othello-GPT Transformer model developed by Kenneth Li et al. Jul 31, 2025 · Contextual hallucinations -- statements unsupported by given context -- remain a significant challenge in AI. With model surgery, we make the Jul 14, 2024 · Marks & Tegmark [39] use linear probes to a truth dimension that can steer an LLM to treat false statements as true and vice versa. Results show that the bias towards simple solutions of generalizing networks is maintained even when statistical irregularities are intentionally introduced. Apr 23, 2024 · Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems. In this paper, we probe the activations of intermediate layers with linear classification and regression. Feb 27, 2025 · Abstract Sparse autoencoders (SAEs) have emerged as a promising approach in language model interpretability, offering unsupervised extraction of sparse features. sma pbcwfrf hlndueywr wugby wtkop gxfje xzqf wsoreb lgvko cmnhwk ewnmy owgvg odchl twirmzg wzwjl