Upload TM-NLA release checkpoints

README.md

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-license: mit
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+# TM-NLA Checkpoints
+
+These checkpoints support the TM-NLA public runtime.
+
+TM-NLA is a proof-of-concept temporal activation-verbalization probe for frozen visual-temporal hidden states. It projects video-window activations from `Qwen/Qwen3.5-0.8B` into a continuous language-oriented manifold, then selects semantic readout hypotheses over time with compatibility and specificity annotations.
+
+## Files
+
+| File | Role | SHA-256 |
+| --- | --- | --- |
+| `temporal_probe.pt` | Temporal visual activation -> continuous language-manifold probe | `48AABF662423EA529C985855EA54970A9CE3256EC3F14AFE0169C2BF1A55B217` |
+| `activation_verbalizer.pt` | Activation -> small set of short candidate readout proposals | `88DDB0267AE535A287755DE5C9E638EB771FFD5C5377051ACFCADF96A98C08C1` |
+| `text_reconstructor.pt` | Text readout -> activation compatibility verifier/reranker | `C5CEA721A2173DCA884617258BB3F671668CF13EBA07728E11C39C9695B5DE32` |
+
+## Base Model
+
+The runtime uses frozen `Qwen/Qwen3.5-0.8B` activations. The public demo path does not train or fine-tune Qwen.
+
+## Intended Use
+
+Use these checkpoints with the TM-NLA GitHub repository to run local terminal-based semantic readouts over video windows.
+
+The checkpoints are intended for interpretability and research exploration. They are not intended as a production captioner, classifier, benchmark system, or broad video-analysis product.
+
+## Limitations
+
+The continuous activation geometry is the strongest result. TM-NLA shows weak recoverable temporal semantic traces from frozen visual-temporal activations. Natural-language readouts are useful but noisy externalizations, not ground-truth captions.
+
+Readouts can be malformed, wrong, generic, or underspecified. The activation verbalizer remains fragile, and candidate generation plus AR reranking is a practical readout mechanism rather than a solved decoder. The text reconstructor is a compatibility-based verifier/reranker, not an oracle. `specificity_status` is a numerical activation-specificity annotation, not a ground-truth correctness label.
+
+## Citation
+
+If you publish work building on this proof of concept, cite or link the companion TM-NLA GitHub repository.

activation_verbalizer.pt

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temporal_probe.pt

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text_reconstructor.pt

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