Release original supervised communication channel checkpoint

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README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model: dllm-hub/Qwen3-0.6B-diffusion-mdlm-v0.1
+tags:
+- pytorch
+- diffusion-language-models
+- multi-agent
+- latent-communication
+- adapter
+- arxiv:2610.28905
+---
+
+# Hidden Messages: Tiny-A2D HM-Synth communication channel
+
+Task-specific, supervised communication-channel weights accompanying
+[Hidden Messages Between Diffusion Language Model Agents: Causal Evidence for Latent Communication](https://arxiv.org/abs/2610.28905),
+accepted at the DiffuLM Workshop at NeurIPS 2026.
+
+This is a communication adapter, **not a standalone language model**. The frozen
+Tiny-A2D backbone is downloaded separately. The adapter consists of a sender-state
+compressor and a gated residual receiver fuser, with four 128-dimensional message
+slots. It was trained on HM-Synth distributed chain-lookup tasks.
+
+## Files and provenance
+
+- `tiny_a2d_channel.pt`: original PyTorch state dictionary.
+- `config.yaml`: original backbone revision, synthetic-task settings, channel
+  architecture, training settings, and evaluation settings.
+- `LICENSE`: Apache-2.0 license for this release's channel weights and documentation.
+- `THIRD_PARTY_LICENSES.md`: attribution for external dependencies and datasets.
+
+These are the existing paper artifacts, mirrored without retraining or checkpoint
+conversion from [the public code release](https://github.com/alanrbtx/hidden-messages-diffusion-agents/tree/1d1477b423ba4245b564840ce46aee039c79bcc8).
+The checkpoint source is `checkpoints/tiny_a2d_channel.pt`.
+No new inference or benchmark validation was performed for this Hub mirror.
+
+## Download
+
+```python
+from huggingface_hub import hf_hub_download
+
+checkpoint_path = hf_hub_download(
+    repo_id="RobotLearningLab/hidden-messages-tiny-a2d",
+    filename="tiny_a2d_channel.pt",
+)
+config_path = hf_hub_download(
+    repo_id="RobotLearningLab/hidden-messages-tiny-a2d",
+    filename="config.yaml",
+)
+```
+
+The download example does not run inference. The original `ReceiverChannel` class
+is defined in
+[`phase5_hm_synth_tiny.py`](https://github.com/alanrbtx/hidden-messages-diffusion-agents/blob/1d1477b423ba4245b564840ce46aee039c79bcc8/code/scripts/phase5_hm_synth_tiny.py),
+with compressor and fusion modules in `code/src/hidden_messages/communication/`.
+Use that architecture and the accompanying config to load the trusted state
+dictionary with `torch.load(..., weights_only=True)`. The original driver includes
+training and evaluation, not just a checkpoint-only inference CLI. This repository
+does not implement Transformers `AutoModel.from_pretrained` or a hosted
+text-generation endpoint.
+
+Required backbone: `dllm-hub/Qwen3-0.6B-diffusion-mdlm-v0.1`, revision
+`c8d24a3f4adaeef46881b450e1bf7d1005203bd7`. Use the pinned dependencies in the code
+repository and a CUDA environment for the reported model workflow. The full
+backbone weights are not included here.
+
+## Scope and limitations
+
+Training uses union-context teacher states and paired matched-versus-deranged
+supervision. Evaluation uses split private contexts. The adapter is task-specific;
+it is not an emergent language, a privacy mechanism, or a demonstrated universal
+cross-task protocol. It should not be assumed interchangeable with the Dream QASC
+adapter. Independent agent trajectories, the designated receiver, and causal
+message interventions are part of the evaluated setup.
+
+For reported results and experimental scope, see the paper and
+[`evidence/tiny_controlled_results.json`](https://github.com/alanrbtx/hidden-messages-diffusion-agents/blob/1d1477b423ba4245b564840ce46aee039c79bcc8/evidence/tiny_controlled_results.json).
+
+## Citation
+
+```bibtex
+@misc{gazzaev2026hiddenmessages,
+  title={Hidden Messages Between Diffusion Language Model Agents: Causal Evidence for Latent Communication},
+  author={Alan-Barsag Gazzaev and Alexey Gavrilov and Sergey Muravyov and Ilya Makarov},
+  year={2026},
+  eprint={2610.28905},
+  archivePrefix={arXiv}
+}
+```

THIRD_PARTY_LICENSES.md

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+# Third-party assets
+
+- **Tiny-A2D / Qwen3-0.6B-diffusion-mdlm-v0.1** — dLLM, Apache License 2.0.
+  Model card: https://huggingface.co/dllm-hub/Qwen3-0.6B-diffusion-mdlm-v0.1
+- **Dream-v0-Instruct-7B** — Dream-org, Apache License 2.0.
+  Paper: https://arxiv.org/abs/2508.15487
+- **QASC** — Khot et al., CC BY 4.0.
+  Paper: https://arxiv.org/abs/1910.11473
+
+The archive does not redistribute the Tiny-A2D or Dream weights or the QASC source dataset.
+Exact pinned revisions remain in the machine-readable configurations and upstream manifest.

config.yaml

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+model:
+  id: dllm-hub/Qwen3-0.6B-diffusion-mdlm-v0.1
+  revision: c8d24a3f4adaeef46881b450e1bf7d1005203bd7
+  dtype: bfloat16
+data:
+  family: distributed_chain_lookup
+  agents: 2
+  hops: [2, 3, 4]
+  distractors_per_agent: 2
+  train_pairs: 5000
+  validation_pairs: 500
+  evaluation_pairs: 1000
+  counterfactual_receiver_context_fixed: true
+channel:
+  message_slots: 4
+  message_dim: 128
+  width: 256
+  attention_heads: 4
+  receiver_interface: gated_residual_fusion
+training:
+  steps: 960
+  batch_size: 64
+  learning_rate: 0.0003
+  weight_decay: 0.01
+  union_teacher_weight: 0.5
+  paired_separation_weight: 0.2
+  paired_batch_fraction: 0.25
+evaluation:
+  batch_size: 128
+  bootstrap_replicates: 5000
+  primary_output: designated_receiver_agent0
+  voting: false

tiny_a2d_channel.pt

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+oid sha256:82062c72ef33aa6bf1518c8b7bebee55292d907bcf4a1eb3b8d33421db6d2171
+size 6359541