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{
"title": "Ropedia Xperience-10M Current Result Versions and Model Groups",
"generated_at_utc": "2026-06-21T10:47:04+00:00",
"status": "pass",
"version_count": 3,
"model_group_count": 5,
"comparison_rule": "Compare only rows with the same scope and target. Single-episode raw-feature metrics, 128-episode metadata baselines, Qwen3 structured JSON metrics, and the two Cosmos3 targets answer different questions: Nano future-window retrieval versus Super structured JSON Reasoner evaluation.",
"version_reading_notes": [
"Version 1 is the public-sample 20-task surface: original core heads, tasks 13-20, and the 180-row method-task matrix.",
"Version 2 is the selected 128-episode same-split simple/NN baseline alignment.",
"The selected-128 model-diagnostic group contains the current Qwen3-Omni LoRA JSON-task row, Cosmos3-Nano future-window compatibility result, Cosmos3-Super Reasoner base-weight JSON-task evaluation, and the separate Cosmos3-Super Forward-Dynamics LoRA adapter artifact."
],
"versions": [
{
"id": "v1_single_episode_public_sample",
"title": "Single-Episode Public-Sample 20-Task Suite",
"status": "verified",
"scope": "one public Xperience-10M sample episode",
"source": "results/episode_task_suite/summary_report.json",
"split": "chronological 70/30 within one episode",
"counts": {
"episodes": 1,
"windows": 1161,
"frames": 5821,
"feature_dim": 8546,
"core_task_count": 12,
"unified_task_count": 20,
"method_task_record_count": 180,
"neural_task_count": 12
},
"models": [
"minimal task heads",
"compact neural MLP task heads"
],
"task_metrics": [
{
"task": "caption_grounding",
"task_display_name": "Language Grounding",
"simple_status": "pass",
"simple_primary_metric": "mrr",
"simple_primary_score": 0.016023479050338015,
"neural_status": "pass",
"neural_primary_metric": "mrr",
"neural_primary_score": 0.01684125567132316
},
{
"task": "contact_prediction",
"task_display_name": "Contact State Prediction",
"simple_status": "pass",
"simple_primary_metric": "macro_f1",
"simple_primary_score": 1.0,
"neural_status": "pass",
"neural_primary_metric": "macro_f1",
"neural_primary_score": 1.0
},
{
"task": "cross_modal_retrieval",
"task_display_name": "Cross-Modal Retrieval",
"simple_status": "pass",
"simple_primary_metric": "mrr",
"simple_primary_score": 0.26925966892956127,
"neural_status": "pass",
"neural_primary_metric": "mrr",
"neural_primary_score": 0.1299971898648288
},
{
"task": "hand_trajectory_forecast",
"task_display_name": "Hand Trajectory Forecasting",
"simple_status": "pass",
"simple_primary_metric": "mpjpe",
"simple_primary_score": 0.8646570444107056,
"neural_status": "pass",
"neural_primary_metric": "mpjpe",
"neural_primary_score": 0.10785018652677536
},
{
"task": "misalignment_detection",
"task_display_name": "Multimodal Synchronization Detection",
"simple_status": "pass",
"simple_primary_metric": "f1",
"simple_primary_score": 0.5051698670605613,
"neural_status": "pass",
"neural_primary_metric": "f1",
"neural_primary_score": 0.7152682255845944
},
{
"task": "modality_reconstruction",
"task_display_name": "Cross-Modal Reconstruction",
"simple_status": "pass",
"simple_primary_metric": "r2",
"simple_primary_score": -0.015271898913936655,
"neural_status": "pass",
"neural_primary_metric": "r2",
"neural_primary_score": -0.010171410134180991
},
{
"task": "next_action",
"task_display_name": "Next-Action Prediction",
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"neural_primary_metric": "macro_f1",
"neural_primary_score": 0.04186046511627907
},
{
"task": "object_relevance",
"task_display_name": "Object Relevance Prediction",
"simple_status": "pass",
"simple_primary_metric": "micro_f1",
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"neural_status": "pass",
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"neural_primary_score": 0.1679279279279279
},
{
"task": "temporal_order",
"task_display_name": "Temporal Order Verification",
"simple_status": "pass",
"simple_primary_metric": "accuracy",
"simple_primary_score": 0.4540229885057471,
"neural_status": "pass",
"neural_primary_metric": "accuracy",
"neural_primary_score": 0.8577586206896551
},
{
"task": "timeline_action",
"task_display_name": "Action Recognition",
"simple_status": "pass",
"simple_primary_metric": "macro_f1",
"simple_primary_score": 0.05,
"neural_status": "pass",
"neural_primary_metric": "macro_f1",
"neural_primary_score": 0.014814814814814814
},
{
"task": "timeline_subtask",
"task_display_name": "Procedure Step Recognition",
"simple_status": "pass",
"simple_primary_metric": "macro_f1",
"simple_primary_score": 0.05056355513846935,
"neural_status": "pass",
"neural_primary_metric": "macro_f1",
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},
{
"task": "transition_detection",
"task_display_name": "Action Boundary Detection",
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"neural_status": "pass",
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}
],
"interpretation": "This layer verifies the original core task contracts, raw multimodal feature pipeline, and unified 20-task public result surface. It is not a cross-episode benchmark."
},
{
"id": "v2_multi_episode_128_aligned_metadata_baselines",
"title": "128-Episode Aligned Simple/NN Baselines",
"status": "pass",
"scope": "selected 128-episode 96/16/16 split",
"source": "results/omni_finetune/multi_episode_128_task_baselines/BASELINE_ALIGNMENT_REPORT.md",
"split": "train/val/test by selected episode/session",
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},
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"simple_supported_task_count": 8,
"neural_supported_task_count": 6
},
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"metadata/text simple baselines",
"metadata/text neural MLP baselines"
],
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{
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{
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{
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},
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"neural_primary_score": 0.0
},
{
"task": "hand_trajectory_forecast",
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"simple_status": "unsupported_without_raw_128_feature_blocks",
"simple_primary_metric": "mpjpe",
"simple_primary_score": null,
"neural_status": "not_run",
"neural_primary_metric": "",
"neural_primary_score": null
},
{
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"neural_status": "pass",
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},
{
"task": "object_relevance",
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"neural_status": "pass",
"neural_primary_metric": "micro_f1",
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},
{
"task": "caption_grounding",
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"neural_status": "not_run",
"neural_primary_metric": "",
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},
{
"task": "cross_modal_retrieval",
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"simple_status": "unsupported_without_raw_128_feature_blocks",
"simple_primary_metric": "mrr",
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"neural_status": "not_run",
"neural_primary_metric": "",
"neural_primary_score": null
},
{
"task": "modality_reconstruction",
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"simple_status": "unsupported_without_raw_128_feature_blocks",
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"neural_status": "not_run",
"neural_primary_metric": "",
"neural_primary_score": null
},
{
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{
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}
],
"interpretation": "This layer aligns the previous simple and neural baseline framing to the same selected 96/16/16 split used by the Qwen3-Omni and Cosmos3 diagnostics. It uses public-safe JSONL metadata/text features, so raw-feature-only tasks remain explicitly unsupported until 128-run sensor feature blocks exist."
},
{
"id": "v3_multi_episode_foundation_model_branches",
"title": "128-Episode Foundation-Model Branches",
"status": "partial_verified",
"scope": "selected 128-episode split and compatible derived windows",
"source": "results/omni_finetune/verified_public/",
"split": "episode/session held-out split; exact task target depends on backbone contract",
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"cosmos3_verified_package_count": 3,
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"cosmos3_super_verified_package_count": 2
},
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"Cosmos3-Nano future-window compatibility branch",
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"Cosmos3-Super forward-dynamics LoRA"
],
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"title": "Cosmos3-Nano Future-Window World Model",
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],
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},
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{
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{
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{
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{
"id": "xperience10m_qwen3_omni_128ep_structured_json_v4_4epoch_full8gpu_lora_eval_test_full",
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{
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{
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}
],
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{
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{
"id": "task_heads_single_episode_public_sample",
"title": "Single-Episode Public-Sample 20-Task Suite",
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"status": "verified",
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}
],
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{
"id": "task_heads_128_episode_metadata_baselines",
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"scope": "selected 128-episode 96/16/16 split",
"status": "pass",
"source": "results/omni_finetune/multi_episode_128_task_baselines/BASELINE_ALIGNMENT_REPORT.md",
"split": "train/val/test by selected episode/session",
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}
],
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},
{
"id": "qwen3_omni_lora",
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{
"id": "qwen3_omni_sensor_adapter_smoke_1ep",
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"scope": "one public Xperience-10M sample episode",
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{
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{
"id": "xperience10m_qwen3_omni_128ep_fullparam_pilot32_preemptible_8gpu_20260609",
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{
"id": "xperience10m_qwen3_omni_128ep_fullparam_pilot64_preemptible_8gpu_20260609",
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"interpretation": "Full-parameter FSDP feasibility evidence only. This gate is not a held-out model result, full fine-tune, checkpoint release, or public weight package."
},
{
"id": "xperience10m_qwen3_omni_128ep_fullparam_pilot128_preemptible_8gpu_20260609",
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"status": "preempted_for_qwen_v5_handoff",
"source": "results/omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_preemptible_8gpu_20260609/fullparam_pilot128_summary.json",
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{
"id": "xperience10m_qwen3_omni_128ep_fullparam_pilot128_after_qwen_v5_preemptible_8gpu_20260609",
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"scope": "128 optimizer steps over 1024 train samples after verified Qwen v5 handoff",
"status": "passed",
"source": "results/omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_after_qwen_v5_preemptible_8gpu_20260609/training_metadata.json",
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{
"id": "xperience10m_qwen3_omni_128ep_fullparam_pilot256_after_qwen_v6_preemptible_8gpu_20260611",
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"status": "passed",
"source": "results/omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot256_after_qwen_v6_preemptible_8gpu_20260611/training_metadata.json",
"split": "selected 128-episode train split",
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"interpretation": "Full-parameter FSDP feasibility evidence only. This gate is not a held-out model result, full fine-tune, checkpoint release, or public weight package."
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],
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{
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},
"history": [],
"is_current": true,
"weights_repository": "none for this run: staged base nv-community/Cosmos3-Super weights were evaluated through vLLM; create a separate repo only after new adapter or fine-tuned weights exist"
}
],
"comparison_note": "Cosmos3-Super is now represented by a verified 448-window held-out Reasoner evaluation on the same JSON task as Qwen3. It uses staged base weights through vLLM, so it is a Cosmos3 diagnostic, not a weight release. A camera-pose proxy forward-dynamics target export now passes the contract audit and schema-only packer smoke; the separate Forward-Dynamics LoRA group records the trainable adapter run and loss-based held-out evaluation."
},
{
"id": "cosmos3_super_forward_dynamics",
"model_family": "Cosmos3-Super Forward-Dynamics LoRA",
"model_type": "PEFT LoRA over nv-community/Cosmos3-Super for camera-pose-conditioned future vision velocity",
"weight_repository": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep",
"one_episode_runs": [
{
"id": "cosmos3_super_forward_dynamics_overfit_smoke",
"title": "Cosmos3-Super Forward-Dynamics Overfit Smoke",
"scope": "small overfit smoke before 128-episode scale-up",
"status": "verified_smoke",
"source": "results/omni_finetune/xperience10m_cosmos3_super_forward_dynamics_lora_overfit_after_qwen_v4_20260608_fsdp8_attn256_gradfix_savefix2/",
"weights": "local repaired LoRA smoke adapter, not public packaged as final",
"interpretation": "Validated the trainable adapter path, FSDP save repair, and Diffusers load before the full 128-episode run."
}
],
"multi_episode_128_runs": [
{
"id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp",
"title": "Cosmos3-Super Forward-Dynamics LoRA",
"status": "verified",
"backbone": "cosmos3_super_forward_dynamics",
"dataset_contract": "xperience10m_camera_pose_forward_dynamics_v1",
"training_objective": "camera_pose_conditioned_future_vision_velocity_lora",
"source": "results/omni_finetune/verified_public/xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp/verified_result_summary.json",
"dataset_run_id": "xperience10m_cosmos3_camera_pose_targets_20260608",
"train_run_id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608",
"eval_run_id": "xperience10m_cosmos3_super_forward_dynamics_lora_128ep_train1epoch_256_attn_full8gpu_20260608_eval_test_full_fsdp",
"counts": {
"dataset_samples": 3808,
"dataset_episodes": 119,
"split_counts": {
"test": 448,
"train": 2848,
"val": 512
},
"train_samples": 2848,
"val_samples": 512,
"eval_samples": 448,
"held_out_episode_count": 14,
"num_processes": 8
},
"primary_metrics": {
"adapter_parameter_numel": 26214400,
"held_out_episode_count": 14,
"test_forward_dynamics_mse": 3.6853174321087345,
"train_final_loss": 1.0785235166549683,
"val_forward_dynamics_mse": 4.008244896889664
},
"history": [
{
"epoch": 1,
"note": "FSDP 8-GPU LoRA over camera-pose-conditioned future vision velocity loss; adapter weights are excluded from this public package.",
"train_loss": 1.0785235166549683,
"val_loss": 4.008244896889664
}
],
"is_current": true,
"weights_repository": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep"
}
],
"comparison_note": "This is the first verified Cosmos3-Super fine-tuned adapter branch. Its metric is forward-dynamics MSE, so compare it to world-model loss or future-prediction targets, not to Qwen JSON classification accuracy."
}
],
"model_group_reading_notes": [
"Use model_groups when comparing one-episode and 128-episode artifacts within the same model family.",
"Task-head baselines have both a one-episode public-sample run and a 128-episode same-split metadata/text run.",
"Qwen3-Omni has a one-episode sensor-adapter smoke test, full-parameter feasibility gates, and separate 128-episode LoRA diagnostic packages; the newest verified full-eval 128-episode adapter belongs in the Qwen LoRA model repo.",
"Cosmos3-Nano has a 128-episode future-window compatibility package.",
"Cosmos3-Super now has both a 128-episode base-weight Reasoner evaluation on the JSON task and a fine-tuned forward-dynamics LoRA branch over camera-pose proxy targets."
],
"pending": [
"Use the verified Qwen3 v6 rank64/lr5e-5 dense multiscale full-eval package as the latest current Qwen row; the v5 release tag remains pinned as the previous verified release.",
"Read results/omni_finetune/QWEN3_V5_V6_COMPARISON_20260614.md before claiming v6 is globally better than v5, because v6 improves action macro-F1 and contact accuracy but regresses subtask, next-action, object micro-F1, and JSON validity slightly."
]
}