fix(leaderboard): align GPT-5.5 Long results and evaluation notes

rpent/benchmarks/leaderboard.js

@@ -124,17 +124,33 @@
     if(id==='robotwin') return lang==='en'?'Clean-to-Randomized Success':'Clean-to-Randomized 成功率';
     return tr(views.get(id).label)+' · '+t('rate');
   }
+  const evaluationNotes = new Map([
+    ['aspire', 1], ['rpent-flash-mode', 2],
+    ['gpt-6-astra-low-motor-only', 3], ['gpt-6-astra-low', 4]
+  ]);
+  const noteId = number => number===4?'libero-pro-astra-memory':`libero-pro-note-${number}`;
+  function noteReference(record) {
+    const section=d.sections.find(s=>s.id==='libero-pro');
+    const number=section.views.includes(record.view_id)?evaluationNotes.get(record.configuration_id):null;
+    if(!number)return '';
+    const description=lang==='en'?`Evaluation note ${number} for ${label(record)}`:`${label(record)}的评测说明 ${number}`;
+    return `<sup class="note-reference"><a href="#${noteId(number)}" role="doc-noteref" aria-label="${h(description)}">[${number}]</a></sup>`;
+  }
+  function noteParagraph(paragraph, number) {
+    const marked=paragraph.startsWith('* ')?`* <span class="note-number">[${number}]</span> ${h(paragraph.slice(2))}`:h(paragraph);
+    return `<p id="${noteId(number)}" class="scope-note${number===4?' memory-context':''}" tabindex="-1" role="note">${marked}</p>`;
+  }
   function chart(view, kind='primary') {
     const rows=allRows(view).filter(r=>r.rate!==null);
     return `<div class="chart ${kind}" aria-label="${h(headline(view.id))}"><div class="chart-grid" aria-hidden="true">${Array.from({length:6},()=>'<i></i>').join('')}</div><div class="chart-rows">${rows.map(r=>
-      `<div class="chart-row" tabindex="0" data-record="${r.id}" aria-label="${h(label(r)+', '+detailLabel(r)+', '+r.rate+'%, '+count(r))}"><div class="method-label"><span class="method-text"><span class="method-name">${h(label(r))}</span><span class="method-description">${h(detailLabel(r))}</span></span></div><div class="bar-track"><div class="bar${Number(r.rate)===0?' zero':''}" style="--value:${Number(r.rate)}%;--bar-color:${color(r,view)}"><span class="bar-value">${r.rate}%</span></div></div></div>`).join('')}</div><div class="axis" aria-hidden="true">${[0,20,40,60,80,100].map(x=>`<span>${x}</span>`).join('')}</div></div>`;
+      `<div class="chart-row" tabindex="0" data-record="${r.id}" aria-label="${h(label(r)+', '+detailLabel(r)+', '+r.rate+'%, '+count(r))}"><div class="method-label"><span class="method-text"><span class="method-name">${h(label(r))}${noteReference(r)}</span><span class="method-description">${h(detailLabel(r))}</span></span></div><div class="bar-track"><div class="bar${Number(r.rate)===0?' zero':''}" style="--value:${Number(r.rate)}%;--bar-color:${color(r,view)}"><span class="bar-value">${r.rate}%</span></div></div></div>`).join('')}</div><div class="axis" aria-hidden="true">${[0,20,40,60,80,100].map(x=>`<span>${x}</span>`).join('')}</div></div>`;
   }
   function comparisonMatrix(s) {
     const columns=s.views.map(id=>views.get(id));
     const rows=d.configurations.filter(c=>columns.some(v=>v.record_ids.some(id=>records.get(id).configuration_id===c.id&&records.get(id).rate!==null)));
     return `<details class="comparison-matrix" data-details="${s.id}"><summary>${t('allScores')} <span>${rows.length} ${lang==='en'?'configurations':'配置'}</span></summary><div class="table-wrap" tabindex="0" role="region" aria-label="${h(s.name+' '+t('allScores'))}"><table><thead><tr><th>${t('method')}</th>${columns.map(v=>`<th class="rate">${h(tr(v.label))}</th>`).join('')}</tr></thead><tbody>${rows.map(c=>{
       const sample=columns.flatMap(allRows).find(r=>r.configuration_id===c.id&&r.rate!==null);
-      return `<tr data-method="${c.id}"><th scope="row"><div class="matrix-label"><span>${h(label(sample))}<small> ${h(detailLabel(sample))}</small></span></div></th>${columns.map(v=>{
+      return `<tr data-method="${c.id}"><th scope="row"><div class="matrix-label"><span>${h(label(sample))}${noteReference(sample)}<small> ${h(detailLabel(sample))}</small></span></div></th>${columns.map(v=>{
         const r=allRows(v).find(r=>r.configuration_id===c.id);
         return `<td class="rate"${r?` data-matrix-record="${r.id}"`:''} title="${h(tr(r?.evaluation_note)||tr(v.label))}">${r?.rate!=null?r.rate+'%':`<span class="not-reported" aria-label="${t('unreported')}">—</span>`}</td>`;
       }).join('')}</tr>`;
@@ -147,7 +163,7 @@
   function renderSection(s) {
     const element=document.getElementById('panel-'+s.id);
     const note=tr(s.notes);
-    element.innerHTML=sectionBody(s)+(note?note.split('\n\n').map(paragraph=>`<p class="scope-note">${h(paragraph)}</p>`).join(''):'')+(s.context?`<p id="${s.id}-astra-memory" class="scope-note memory-context">${h(tr(s.context))}</p>`:'');
+    element.innerHTML=sectionBody(s)+(note?note.split('\n\n').map((paragraph,index)=>noteParagraph(paragraph,index+1)).join(''):'')+(s.context?noteParagraph(tr(s.context),4):'');
     setupTables(element,s.id);
   }
   function setupTables(element,key) {
@@ -274,6 +290,7 @@
     const anchor=e.target.closest('a[href^="#"]');
     if(anchor&&document.getElementById(normalizeAnchor(anchor.hash))){
       e.preventDefault();navigate(normalizeAnchor(anchor.hash),true);
+      if(anchor.closest('.note-reference'))document.getElementById(normalizeAnchor(anchor.hash)).focus({preventScroll:true});
     }
     const summary=e.target.closest('.module-header');
     if(summary)markModule(summary.parentElement.dataset.module);

rpent/benchmarks/results.json

@@ -1,6 +1,6 @@
 {
   "schema_version": 2,
-  "checked_at": "2026-09-18",
+  "checked_at": "2026-09-22",
   "paper_revision": "2607.08448v4",
   "repository_revision": "43f32aa08cba07bd4d49a4bfa5eba4ef633e9b92",
   "configurations": [
@@ -843,13 +843,13 @@
       "view_id": "long-task",
       "configuration_id": "gpt-5-5-xhigh",
       "status": "reported",
-      "rate": "52.0",
-      "successes": null,
+      "rate": "70.00",
+      "successes": 70,
       "episodes": 100,
       "source_ids": [
-        "paper-table-3"
+        "repo-libero-long-reproduction-20260922"
       ],
-      "protocol_id": "rpent-pro"
+      "protocol_id": "rpent-pro-long-reproduction"
     },
     {
       "id": "long-task--gpt-6-astra-low",
@@ -870,13 +870,13 @@
       "view_id": "long-swap",
       "configuration_id": "gpt-5-5-xhigh",
       "status": "reported",
-      "rate": "49.0",
-      "successes": null,
+      "rate": "55.00",
+      "successes": 55,
       "episodes": 100,
       "source_ids": [
-        "paper-table-3"
+        "repo-libero-long-reproduction-20260922"
       ],
-      "protocol_id": "rpent-pro"
+      "protocol_id": "rpent-pro-long-reproduction"
     },
     {
       "id": "long-swap--gpt-6-astra-low",
@@ -896,14 +896,25 @@
       "id": "libero-pro--gpt-5-5-xhigh",
       "view_id": "libero-pro",
       "configuration_id": "gpt-5-5-xhigh",
-      "status": "reported",
-      "rate": "72.1",
+      "status": "derived",
+      "rate": "75.13",
       "successes": null,
       "episodes": 800,
       "source_ids": [
-        "paper-table-3"
+        "paper-table-3",
+        "repo-libero-long-reproduction-20260922"
       ],
-      "protocol_id": "rpent-pro"
+      "protocol_id": "rpent-pro-updated-long",
+      "derived_from": [
+        "spatial-task--gpt-5-5-xhigh",
+        "spatial-swap--gpt-5-5-xhigh",
+        "object-task--gpt-5-5-xhigh",
+        "object-swap--gpt-5-5-xhigh",
+        "goal-task--gpt-5-5-xhigh",
+        "goal-swap--gpt-5-5-xhigh",
+        "long-task--gpt-5-5-xhigh",
+        "long-swap--gpt-5-5-xhigh"
+      ]
     },
     {
       "id": "libero-pro--gpt-6-astra-low",
@@ -3211,6 +3222,17 @@
       "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": {
@@ -3351,8 +3373,8 @@
         "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。"
+        "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": [
@@ -3367,8 +3389,8 @@
         "long-swap"
       ],
       "notes": {
-        "en": "ASPIRE: Long Task and Long Swap use zero-shot transfer from the LIBERO-90 skill library.\n\nRPent / 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\nRPent / 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"
+        "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。"
       }
     },
     {

rpent/benchmarks/table-sort.js

@@ -33,10 +33,16 @@
       if(state.highlightBest&&column!==state.idColumn&&maximum!==null&&valueOf(row.cells[column])===maximum)row.cells[column].classList.add('metric-best');
     }
   }
+  function exportText(cell) {
+    const copy=cell.cloneNode(true);
+    copy.querySelectorAll('.note-reference').forEach(marker=>marker.remove());
+    const text=copy.textContent.trim();
+    return text==='—'?'':text;
+  }
   function exportTable(table) {
     const quote=v=>'"'+String(v??'').replaceAll('"','""')+'"';
     const state=table._rpentSort;
-    const rows=[state.headers.map(th=>th.dataset.label),...[...table.tBodies[0].rows].map(row=>[...row.cells].map(cell=>cell.textContent.trim()==='—'?'':cell.textContent.trim()))];
+    const rows=[state.headers.map(th=>th.dataset.label),...[...table.tBodies[0].rows].map(row=>[...row.cells].map(exportText))];
     const url=URL.createObjectURL(new Blob(['\uFEFF'+rows.map(row=>row.map(quote).join(',')).join('\r\n')],{type:'text/csv;charset=utf-8'}));
     const a=document.createElement('a');a.href=url;a.download=state.key.replaceAll(/[^a-zA-Z0-9-]/g,'-')+'.csv';a.click();
     setTimeout(()=>URL.revokeObjectURL(url),3000);