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null, "episodes": 500, "source_ids": [ "aspire-table-5" ], "protocol_id": "aspire-libero90-zero-shot", "evaluation_note": { "en": "Long zero-shot transfer (LIBERO-90 library)", "zh": "Long 零样本迁移（LIBERO-90 技能库）" } }, { "id": "long-swap--aspire", "view_id": "long-swap", "configuration_id": "aspire", "status": "reported", "rate": "22.6", "successes": null, "episodes": 500, "source_ids": [ "aspire-table-5" ], "protocol_id": "aspire-libero90-zero-shot", "evaluation_note": { "en": "Long zero-shot transfer (LIBERO-90 library)", "zh": "Long 零样本迁移（LIBERO-90 技能库）" } }, { "id": "libero-pro--aspire", "view_id": "libero-pro", "configuration_id": "aspire", "status": "derived", "rate": "61.36", "successes": null, "episodes": null, "source_ids": [ "aspire-table-2", "aspire-table-5" ], "protocol_id": "aspire-eight-component-mean", "derived_from": [ "spatial-task--aspire", "spatial-swap--aspire", "object-task--aspire", "object-swap--aspire", "goal-task--aspire", "goal-swap--aspire", "long-task--aspire", 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"contributor-qwen-costs-20260918" ], "protocol_id": "rpent-pro-qwen-eight-suites" }, { "id": "spatial-swap--qwen3-6-27b-no-reasoning", "view_id": "spatial-swap", "configuration_id": "qwen3-6-27b-no-reasoning", "status": "reported", "rate": "78.00", "successes": 78, "episodes": 100, "source_ids": [ "contributor-qwen-costs-20260918" ], "protocol_id": "rpent-pro-qwen-eight-suites" }, { "id": "object-task--qwen3-6-27b-no-reasoning", "view_id": "object-task", "configuration_id": "qwen3-6-27b-no-reasoning", "status": "reported", "rate": "83.00", "successes": 83, "episodes": 100, "source_ids": [ "contributor-qwen-costs-20260918" ], "protocol_id": "rpent-pro-qwen-eight-suites" }, { "id": "object-swap--qwen3-6-27b-no-reasoning", "view_id": "object-swap", "configuration_id": "qwen3-6-27b-no-reasoning", "status": "reported", "rate": "84.00", "successes": 84, "episodes": 100, "source_ids": [ "contributor-qwen-costs-20260918" ], "protocol_id": "rpent-pro-qwen-eight-suites" }, { "id": "goal-task--qwen3-6-27b-no-reasoning", "view_id": "goal-task", "configuration_id": "qwen3-6-27b-no-reasoning", "status": "reported", "rate": "68.00", "successes": 68, "episodes": 100, "source_ids": [ "contributor-qwen-costs-20260918" ], "protocol_id": "rpent-pro-qwen-eight-suites" }, { "id": "goal-swap--qwen3-6-27b-no-reasoning", "view_id": "goal-swap", "configuration_id": "qwen3-6-27b-no-reasoning", "status": "reported", "rate": "68.00", "successes": 68, "episodes": 100, "source_ids": [ "contributor-qwen-costs-20260918" ], "protocol_id": "rpent-pro-qwen-eight-suites" }, { "id": "long-task--qwen3-6-27b-no-reasoning", "view_id": "long-task", "configuration_id": "qwen3-6-27b-no-reasoning", "status": "reported", "rate": "61.00", "successes": 61, "episodes": 100, "source_ids": [ "contributor-qwen-costs-20260918" ], "protocol_id": "rpent-pro-qwen-eight-suites" }, { "id": "long-swap--qwen3-6-27b-no-reasoning", "view_id": "long-swap", "configuration_id": "qwen3-6-27b-no-reasoning", "status": "reported", "rate": "41.00", "successes": 41, "episodes": 100, "source_ids": [ "contributor-qwen-costs-20260918" ], "protocol_id": "rpent-pro-qwen-eight-suites" }, { "id": "long-task--gpt-6-astra-low-motor-only", "view_id": "long-task", "configuration_id": "gpt-6-astra-low-motor-only", "status": "reported", "rate": "38.0", "successes": 38, "episodes": 100, "source_ids": [ "contributor-motor-only-long-task-20260920" ], "protocol_id": "rpent-pro-motor-only" } ], "sources": [ { "id": "paper-table-2", "url": "https://arxiv.org/html/2607.08448v4#S3.T2" }, { "id": "paper-table-3", "url": "https://arxiv.org/html/2607.08448v4#S3.T3" }, { "id": "paper-table-4", "url": "https://arxiv.org/html/2607.08448v4#S3.T4" }, { "id": "paper-table-6", "url": "https://arxiv.org/html/2607.08448v4#S3.T6" }, { "id": "astra-long-20260907", "report_sha256": "627d6d8a95fb1e10357961694867cd0bf0a2aa9011c96c8a33504b904cb96c80" }, { "id": "astra-pro-remaining-20260913", "report_sha256": "627d6d8a95fb1e10357961694867cd0bf0a2aa9011c96c8a33504b904cb96c80" }, { "id": "contributor-20260915", "kind": "contributor-confirmed" }, { "id": "contributor-settings-20260915", "kind": "contributor-confirmed" }, { "id": "contributor-correction-20260916", "kind": "contributor-confirmed", "note": "Corrected model labels and aggregate scores; removed requested configurations. No missing suite scores inferred." }, { "id": "repo-flash-mode-800", "url": "https://github.com/RLinf/RPent/blob/c19727c7bbdd277cd86a985aae3f2741ba01df7a/docs/source-en/rst_source/usage/task_card.rst", "note": "581 successes across all 800 LIBERO-PRO cases; missing source traces count as failures. Molmo is used for visual localization, not planning." }, { "id": "repo-robotwin-20260915", "url": "https://github.com/RLinf/RPent/blob/849143bf740a562367345cec0de9ef4657dafd73/docs/source-en/rst_source/usage/robotwin.rst" }, { "id": "xiaomi-official-robocasa365", "url": "https://robocasa.ai/leaderboard.html", "submission_url": "https://github.com/robocasa-benchmark/leaderboard/blob/main/submissions_md/Xiaomi-Robotics_2026_07_08.md", "checked_at": "2026-09-16", "environment_split": "pretrain", "note": "Published 50-task benchmark scores. Displayed alongside RPent by request; protocol equivalence has not been verified. Episode counts for this reported batch are unspecified here." }, { "id": "xiaomi-paper-v2-table-3", "url": "https://arxiv.org/html/2607.15330v2#S3.T3" }, { "id": "aspire-table-2", "url": "https://arxiv.org/html/2607.00272v1#A2.T2", "note": "Table 2 main LIBERO-Pro results; Pos maps to Swap, Task maps to Task. Ten tasks and seeds 1-50 per suite. Published rounded rates are preserved, not converted to integer successes. Six-item Overall 72% is not an eight-suite Overall." }, { "id": "aspire-table-5", "url": "https://arxiv.org/html/2607.00272v1#A3.T5", "note": "Table 5, N=90 zero-shot library transfer: Task 0.383, Pos 0.226. A different evaluation regime from the six main suites; no combined Overall is inferred." }, { "id": "flash-published-family-counts", "url": "https://github.com/RLinf/misc/blob/main/rpent/task_card/task_card_libero_pro_performance_time.png", "note": "Exact printed titles: Spatial 149/200, Object 179/200, Goal 139/200, Long 114/200. Sum 581/800. Cross-check only; independent Task/Swap scores come from contributor outcome records, not digitized bar heights." }, { "id": "molmo2-model-card", "url": "https://huggingface.co/allenai/Molmo2-8B", "note": "Official model identity. RPent uses Molmo2-8B for visual localization only." }, { "id": "flash-contributor-800-outcomes", "type": "contributor_archive", "artifact": "task_card.zip", "sha256": "a997e5a0f823abf2402e1374e22a068c43dfecc35a778a185d0274efd45e31e2", "note": "Eight Task/Swap aggregates from 800 unique contributor result.json cases, checked against summary.json and published family totals. Each component includes all 100 expected cases (task IDs 0–9, seeds 0–9). The 20 no-card cases remain in the denominator and are not counted as successes.", "aggregates": { "spatial_task": { "successes": 79, "episodes": 100, "outcomes": { "success": 79, "failure": 21 }, "rate": "79.00" }, "spatial_swap": { "successes": 70, "episodes": 100, "outcomes": { "success": 70, "failure": 30 }, "rate": "70.00" }, "object_task": { "successes": 86, "episodes": 100, "outcomes": { "success": 86, "failure": 14 }, "rate": "86.00" }, "object_swap": { "successes": 93, "episodes": 100, "outcomes": { "success": 93, "failure": 7 }, "rate": "93.00" }, "goal_task": { "successes": 74, "episodes": 100, "outcomes": { "failure": 26, "success": 74 }, "rate": "74.00" }, "goal_swap": { "successes": 65, "episodes": 100, "outcomes": { "no_card": 10, "failure": 25, "success": 65 }, "rate": "65.00" }, "long_task": { "successes": 60, "episodes": 100, "outcomes": { "success": 60, "failure": 40 }, "rate": "60.00" }, "long_swap": { "successes": 54, "episodes": 100, "outcomes": { "success": 54, "failure": 36, "no_card": 10 }, "rate": "54.00" } } }, { "id": "robocasa-astra-contributor-correction-20260920", "kind": "contributor_correction", "checked_at": "2026-09-20", "protocol_url": "https://github.com/RLinf/RPent/blob/d14afccce78fb1bdbeba564fdd3ce7984c71bf2e/docs/source-en/rst_source/usage/robocasa.rst#harness-vla-target50-reproduction-protocol", "environment_split": "target", "tasks": 50, "episodes": 340, "groups": { "atomic": { "tasks": 18, "episodes": 180 }, "composite_seen": { "tasks": 16, "episodes": 80 }, "composite_unseen": { "tasks": 16, "episodes": 80 } }, "note": "The contributor corrected the full evaluation to 340 cells on 2026-09-20. Split denominators follow the existing RPent Target50 matrix (180/80/80). Reported success rates remain unchanged; full-run success counts are not inferred from rounded or task-weighted rates. The earlier archive is retained as historical local evidence, not as verification of the corrected full-run counts." }, { "id": "contributor-qwen-costs-20260918", "type": "contributor_report", "note": "Contributor-provided Qwen eight-suite counts and cost table. Mean elapsed time includes all evaluation episodes (success, failure, and timeout); tokens count evaluation-stage output only. No unreported planner, hardware, or token accounting details are inferred." }, { "id": "contributor-motor-only-long-task-20260920", "type": "contributor_report", "note": "Contributor-reported complete Long Task evaluation on another server: 38 successes in 100 episodes. Codex / GPT-6 Astra / low reasoning; execute_action motor-only control without VLA / primitives or memory. This aggregate is independent of the incomplete local motor-only campaign; no unreported suite, runtime, or token measurements are inferred." }, { "id": "repo-libero-long-reproduction-20260922", "url": "https://github.com/RLinf/RPent/blob/15420b438e3adbf82e6640799a0668a2609e3bb7/docs/source-en/rst_source/usage/libero.rst#reproducing-results", "note": "Codex / GPT-5.5 / xhigh reproduction on reproduce/libero reports Long Task 70/100 and Long Swap 55/100. The updated leaderboard combines these two results with the six unchanged Table 3 suites: (81+69+94+91+75+66+70+55)/8 = 75.125%, displayed as 75.13%. This derived Overall is not the paper's original aggregate." }, { "id": "flash-memory-confirmation-20260922", "kind": "contributor-confirmed", "url": "https://huggingface.co/datasets/RLinf/RPent-memory", "note": "The contributor confirms that the displayed Flash Mode evaluation uses directly downloaded, officially released GPT-5.5 exploration memory and the best-performing seed from s0-s9. Molmo2-8B is used for visual localization. No memory snapshot revision is inferred." } ], "astra": { "completed": 800, "successes": 741, "failures": 59, "overall_rate": "92.63", "memory_batches": [ { "campaign_id": "libero_long_gpt6_astra_20260907", "suites": [ "long-task", "long-swap" ] }, { "campaign_id": "libero_pro_remaining_gpt6_astra_20260913", "suites": [ "spatial-task", "spatial-swap", "object-task", "object-swap", "goal-task", "goal-swap" ], "manifest_sha256": "f08702d7c13d9b40a3127b64765ad4d336d022be028396d5f873d7fc4c4c4928" } ], "suites": [ { "view_id": "spatial-task", "suite": "Spatial Task", "dataset": "libero_spatial_task", "completed": 100, "planned": 100, "successes": 100, "failures": 0, "remaining": 0, "rate": "100.00", "status": "complete" }, { "view_id": "spatial-swap", "suite": "Spatial Swap", "dataset": "libero_spatial_swap", "completed": 100, "planned": 100, "successes": 98, "failures": 2, "remaining": 0, "rate": "98.00", "status": "complete" }, { "view_id": "object-task", "suite": "Object Task", "dataset": "libero_object_task", "completed": 100, "planned": 100, "successes": 100, "failures": 0, "remaining": 0, "rate": "100.00", "status": "complete" }, { "view_id": "object-swap", "suite": "Object Swap", "dataset": "libero_object_swap", "completed": 100, "planned": 100, "successes": 99, "failures": 1, "remaining": 0, "rate": "99.00", "status": "complete" }, { "view_id": "goal-task", "suite": "Goal Task", "dataset": "libero_goal_task", "completed": 100, "planned": 100, "successes": 88, "failures": 12, "remaining": 0, "rate": "88.00", "status": "complete" }, { "view_id": "goal-swap", "suite": "Goal Swap", "dataset": "libero_goal_swap", "completed": 100, "planned": 100, "successes": 99, "failures": 1, "remaining": 0, "rate": "99.00", "status": "complete" }, { "view_id": "long-task", "suite": "Long Task", "dataset": "libero_10_task", "completed": 100, "planned": 100, "successes": 85, "failures": 15, "remaining": 0, "rate": "85.00", "status": "complete" }, { "view_id": "long-swap", "suite": "Long Swap", "dataset": "libero_10_swap", "completed": 100, "planned": 100, "successes": 72, "failures": 28, "remaining": 0, "rate": "72.00", "status": "complete" } ] }, "sections": [ { "id": "libero-pro", "name": "LIBERO-PRO", "heading": { "en": "Eight-suite evaluation", "zh": "八套件评测" }, "summary": { "en": "Astra · low · reasoning: 92.63% (741/800)", "zh": "Astra · low · reasoning：92.63%（741/800）" }, "context": { "en": "* GPT-6 Astra (memory-enabled configuration): Long Task/Swap and the other six suites use separate memory-file snapshots frozen after their respective exploration phases, with no updates during evaluation. Overall combines two non-overlapping batches: Long 157/200 plus the other suites 584/600, giving 741/800 (92.63%); the 800 episodes do not share a single memory snapshot.", "zh": "* GPT-6 Astra（使用 memory 的配置）：Long Task/Swap 与其余六套件使用各自探索后冻结的 memory 文件快照，评测期间不更新。Overall 合并两个不重叠批次：Long 157/200，加上其余套件 584/600，得到 741/800（92.63%）；并非全部回合共享同一份 memory 快照。" }, "default_view": "libero-pro", "views": [ "libero-pro", "spatial-task", "spatial-swap", "object-task", "object-swap", "goal-task", "goal-swap", "long-task", "long-swap" ], "notes": { "en": "* ASPIRE: Long Task and Long Swap use zero-shot transfer from the LIBERO-90 skill library.\n\n* RPent Flash Mode uses directly downloaded, officially released GPT-5.5 exploration memory; Molmo2-8B is used for visual localization. These results use the best-performing seed from s0-s9.\n\n* RPent / GPT-6 Motor Only uses motor-only control: it directly outputs end-effector pose increments and gripper commands through execute_action, without invoking VLA / primitives or loading memory.", "zh": "* ASPIRE：Long Task 和 Long Swap 使用 LIBERO-90 技能库进行 zero-shot 迁移。\n\n* RPent Flash Mode 使用直接下载的、官方公开的 GPT-5.5 explore memory；Molmo2-8B 用于视觉定位。该测试结果使用了 s0-s9 中表现最好的 seed。\n\n* RPent / GPT-6 Motor Only 为纯电机控制方法，通过 execute_action 直接输出末端位姿增量与夹爪指令，不调用 VLA / primitive，不加载 memory。" } }, { "id": "standard-libero", "name": "LIBERO", "heading": { "en": "Four-suite evaluation", "zh": "四套件评测" }, "default_view": "standard-libero", "views": [ "standard-libero", "standard-spatial", "standard-object", "standard-goal", "standard-long" ] }, { "id": "robocasa", "name": "RoboCasa365 · Target50", "heading": { "en": "50 tasks · task-weighted Overall", "zh": "50 个任务 · Overall 按任务等权" }, "default_view": "robocasa", "views": [ "robocasa", "robocasa-atomic-seen", "robocasa-composite-seen", "robocasa-composite-unseen" ] }, { "id": "robotwin", "name": "RoboTwin", "heading": { "en": "Clean → Randomized", "zh": "Clean → Randomized" }, "summary": { "en": "50 tasks · 250 episodes", "zh": "50 个任务 · 250 回合" }, "default_view": "robotwin", "views": [ "robotwin" ] } ], "assets": [ "ellipsis.svg", "download.svg", "arrow-down.svg" ], "cost_method_order": [ "gpt-6-astra-low", "gpt-5-6-xhigh", "gpt-5-6-no-reasoning", "rpent-flash-mode", "qwen3-6-27b-no-reasoning" ], "cost_results": [ { "id": "libero-pro--gpt-5-6-xhigh", "benchmark_id": "libero-pro", "configuration_id": "gpt-5-6-xhigh", "mean_elapsed_seconds": 529.23, "total_output_tokens": 3635426, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "libero-pro--gpt-5-6-no-reasoning", "benchmark_id": "libero-pro", "configuration_id": "gpt-5-6-no-reasoning", "mean_elapsed_seconds": 344.17, "total_output_tokens": 2569676, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "libero-pro--gpt-6-astra-low", "benchmark_id": "libero-pro", "configuration_id": "gpt-6-astra-low", "mean_elapsed_seconds": 412.14, "total_output_tokens": 3364938, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "libero-pro--qwen3-6-27b-no-reasoning", "benchmark_id": "libero-pro", "configuration_id": "qwen3-6-27b-no-reasoning", "mean_elapsed_seconds": 626.3, "total_output_tokens": 3270754, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "libero-pro--rpent-flash-mode", "benchmark_id": "libero-pro", "configuration_id": "rpent-flash-mode", "mean_elapsed_seconds": 60.19, "total_output_tokens": 0, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "robocasa--gpt-5-6-xhigh", "benchmark_id": "robocasa", "configuration_id": "gpt-5-6-xhigh", "mean_elapsed_seconds": 1197.56, "total_output_tokens": 5258391, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "robocasa--gpt-5-6-no-reasoning", "benchmark_id": "robocasa", "configuration_id": "gpt-5-6-no-reasoning", "mean_elapsed_seconds": 1013.21, "total_output_tokens": 4792104, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "robocasa--gpt-6-astra-low", "benchmark_id": "robocasa", "configuration_id": "gpt-6-astra-low", "mean_elapsed_seconds": 1168.95, "total_output_tokens": 5894436, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "robotwin--gpt-5-6-xhigh", "benchmark_id": "robotwin", "configuration_id": "gpt-5-6-xhigh", "mean_elapsed_seconds": 1828.7, "total_output_tokens": 4763915, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "robotwin--gpt-5-6-no-reasoning", "benchmark_id": "robotwin", "configuration_id": "gpt-5-6-no-reasoning", "mean_elapsed_seconds": 957.4, "total_output_tokens": 2456401, "source_ids": [ "contributor-qwen-costs-20260918" ] }, { "id": "robotwin--gpt-6-astra-low", "benchmark_id": "robotwin", "configuration_id": "gpt-6-astra-low", "mean_elapsed_seconds": 1078.8, "total_output_tokens": 2763641, "source_ids": [ "contributor-qwen-costs-20260918" ] } ] }