{
"$type": "site.standard.document",
"bskyPostRef": {
"cid": "bafyreic5fta35jask4ktwlqhvgenhytlxe6gdagslk2g5ybpphk6woiciu",
"uri": "at://did:plc:pgryn3ephfd2xgft23qokfzt/app.bsky.feed.post/3mpojrbrkicg2"
},
"path": "/t/research-from-functional-geometry-to-dynamic-grammar-new-limen-audits-v23-v24-across-7-architectures/177260#post_3",
"publishedAt": "2026-07-02T15:17:22.000Z",
"site": "https://discuss.huggingface.co",
"textContent": "This is an incredibly thorough and constructive analysis. Thank you for taking the time to map the literature and design these diagnostic tracks. You’ve pinpointed exactly where the rigor needs to tighten: distinguishing structural depth artifacts from functional dynamic regimes.\nI fully agree that “activation-derived coarse-state transition model” is a more precise framing than “symbolic grammar” at this stage. I’m currently diving into Markovian Circuit Tracing and PoLLMgraph as suggested they seem like perfect anchors for the next iteration.\nYour point about the Depth Baseline is critical. If B→A→D is just a proxy for layer order, the finding is trivial. I am setting up the Track B diagnostics you proposed:\nShuffled-layer transitions to test against structural ordering.\nLayer-centered/z-scored states to remove scale/mean biases.\nCorrelating State D with logit entropy and top-token margin to validate the “Decision/Commitment” label functionally.\nI also appreciate the note on HF extraction quirks (model.generate vs model). I’ll double-check my extraction contract for Qwen/Llama to ensure consistency.\nI’m moving forward with V24.2: Controls & Baselines to address these exact points. The goal is to prove that these motifs survive depth, entropy, and format controls. I’ll share the results of these ablations soon.\nThanks again for pushing the standard higher. This is exactly the kind of scrutiny that makes independent research robust.\nBest,\nJean-Denis",
"title": "[Research] From Functional Geometry to Dynamic Grammar: New LIMEN Audits (V23–V24) Across 7 Architectures"
}