.</p>\n","updatedAt":"2026-09-09T07:20:42.037Z","author":{"_id":"65eb429733c27925394a4be0","avatarUrl":"/avatars/1010b01ba573468c7f66fabdd87c07d7.svg","fullname":"Mika Okamoto","name":"mokamoto","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":1,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"fr","probability":0.32275810837745667},"editors":["mokamoto"],"editorAvatarUrls":["/avatars/1010b01ba573468c7f66fabdd87c07d7.svg"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2609.07139","authors":[{"_id":"6aa0fa2ed0174964227bee4f","user":{"_id":"65eb429733c27925394a4be0","avatarUrl":"/avatars/1010b01ba573468c7f66fabdd87c07d7.svg","isPro":false,"fullname":"Mika Okamoto","user":"mokamoto","type":"user","name":"mokamoto"},"name":"Mika Okamoto","status":"claimed_verified","statusLastChangedAt":"2026-09-09T08:45:04.773Z","hidden":false},{"_id":"6aa0fa2ed0174964227bee50","name":"Gabriele Sarti","hidden":false}],"publishedAt":"2026-09-07T00:00:00.000Z","submittedOnDailyAt":"2026-09-09T00:00:00.000Z","title":"Encoded Early, Used Late: Where Transformers Begin to Act on an Inferred Partner's Expertise","submittedOnDailyBy":{"_id":"65eb429733c27925394a4be0","avatarUrl":"/avatars/1010b01ba573468c7f66fabdd87c07d7.svg","isPro":false,"fullname":"Mika Okamoto","user":"mokamoto","type":"user","name":"mokamoto"},"summary":"A transformer can make an attribute linearly decodable in its residual stream at a depth where that attribute does not yet influence the output. This gap between where information is readable and where it is used has been shown for attributes stated directly in the input. We ask whether it also holds for an attribute the model must infer gradually over a conversation, namely how expert its dialogue partner is. Using ExpertCollab, a corpus of multi-turn research-planning dialogues between model-played personas at four expertise levels, we find that partner expertise is most decodable in the early layers and falls to near chance before the midpoint of the network. Counterfactual patching shows that injecting the expertise difference at the layer of peak decodability barely changes a fixed late-layer readout, whereas the same difference injected past the midpoint propagates almost completely, a separation of more than an order of magnitude. A content-matched random control and a probe-free diagnostic place the transition at the same early layer, and a statically specified control attribute stays decodable throughout. An inferred relational attribute is therefore represented well before it becomes causally active, which bounds where any attempt to read out or steer partner-conditioned behavior must intervene. We use one model on a synthetic corpus as an initial demonstration.","upvotes":15,"discussionId":"6aa0fa2ed0174964227bee51","ai_summary":"In multi-turn dialogues, a model's inference of a partner's expertise becomes readable in early layers but only causally active later, bounding intervention points for steering behavior.","ai_keywords":["transformer","residual stream","linear decodability","counterfactual patching","expert collaboration","relational attribute","causal mediation","probe-free diagnostic"],"ai_summary_model":"thinkingmachines/Inkling-Small"},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[{"_id":"65eb429733c27925394a4be0","avatarUrl":"/avatars/1010b01ba573468c7f66fabdd87c07d7.svg","isPro":false,"fullname":"Mika Okamoto","user":"mokamoto","type":"user"},{"_id":"6a6aa0e36039a754565fcddd","avatarUrl":"/avatars/c7311ecd8157d7f286dfd82f4d33d711.svg","isPro":false,"fullname":"Barbara Taylor","user":"Meridian-Owen","type":"user"},{"_id":"6a6c7cc86c4896078fec71b5","avatarUrl":"/avatars/4cf98265c1ead1bdac6e770c404f8814.svg","isPro":false,"fullname":"Michael White","user":"Vector-Beacon","type":"user"},{"_id":"6a6decb777d1834fc3f24f6a","avatarUrl":"/avatars/a1ea3a5a6361e8ff75699ffa4f970007.svg","isPro":false,"fullname":"David Thomas","user":"Wild-Remy","type":"user"},{"_id":"6a7d48bf05b6bd357d677065","avatarUrl":"/avatars/477d5908e7bbb4bbf1b1b12bfec7446f.svg","isPro":false,"fullname":"QuietDawn","user":"QuietDawn","type":"user"},{"_id":"6a9aed5a0771087c6bf298f6","avatarUrl":"/avatars/bd2568219762942d2fe8db3cf29dda76.svg","isPro":false,"fullname":"李军","user":"guyang90","type":"user"},{"_id":"63ac5701c21e60a3e9b58aa7","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/63ac5701c21e60a3e9b58aa7/g6EX7diOpuA94R2ab-rZC.png","isPro":true,"fullname":"Dipankar Sarkar","user":"dipankarsarkar","type":"user"},{"_id":"6aa0e047d10482233c894792","avatarUrl":"/avatars/3fd514ff257972b096ae6b90b3ee7c2b.svg","isPro":false,"fullname":"牟亮","user":"graniteIan","type":"user"},{"_id":"6aa0f882c250d3fd685c945d","avatarUrl":"/avatars/e0580e078212e6c9c69fcaa25d048a5d.svg","isPro":false,"fullname":"Christopher Stephens","user":"kayleehoover114","type":"user"},{"_id":"6a6c80bbd4a0d27fe1ffa4d2","avatarUrl":"/avatars/bba0d7767c51c3e48a447c0659925e0b.svg","isPro":false,"fullname":"Mary Lopez","user":"Mary-Lopez","type":"user"},{"_id":"6a6c8e41ddefa50419e0eab4","avatarUrl":"/avatars/f7731c21169091f5386a4e3712366620.svg","isPro":false,"fullname":"Richard Johnson","user":"Indigo-Mika","type":"user"},{"_id":"6a7d48310c1402bef2fc5599","avatarUrl":"/avatars/ab67223c9a33083bd0355d90662c9b65.svg","isPro":false,"fullname":"Mary Davis","user":"Quiet-Mary","type":"user"}],"acceptLanguages":["en"],"dailyPaperRank":0,"markdownContentUrl":"https://huggingface.co/buckets/huggingchat/papers-content/resolve/2609/2609.07139.md","query":{}}">

hf papers read 2609.07139

curl -LsSf https://hf.co/cli/install.sh | bash