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Overall, we show that LMs retrieve entities not through a single positional mechanism, but a mixture of three: positional, lexical, and reflexive. Understanding these mechanisms helps explain both the strengths and limits of LLMs, and how they reason in context. 8/
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This was a joint work with the amazing @megamor2.bsky.social and Atticus Geiger. Check out our *interactive blog post* to see how these mechanisms shape LM outputs 👇 🌐 yoav.ml/blog/2025/m... 📄 arxiv.org/abs/2510.06182 🤗 huggingface.co/papers/2510... 💻 github.com/yoavgur/mix...
github.comGitHub - yoavgur/mixing-mechs: Official code for "Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Context"Official code for "Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Context" - yoavgur/mixing-mechs