code/docs/i18n.js

/* Echo-Memory project page — EN / ZH strings */
window.ECHO_I18N = {
  en: {
    "meta.title": "Echo-Memory | Echo Team",
    "meta.description": "Echo-Memory: A controlled study of memory mechanisms in action-conditioned world models.",
    "nav.home": "Home",
    "nav.overview": "Overview",
    "nav.design": "Design",
    "nav.checkpoints": "Ckpt",
    "nav.eval": "Eval",
    "nav.evidence": "Qual",
    "nav.findings": "Results",
    "nav.updates": "Updates",
    "nav.bibtex": "BibTeX",
    "nav.developer": "Dev Guide",
    "nav.github": "GitHub",
    "nav.menu": "Menu",
    "lang.toggle": "中文",
    "lang.current": "EN",
    "lang.switch": "Switch language",
    "hero.badge": "Echo Team · Joy Future Academy, JD · June 2026 · CC BY 4.0",
    "hero.title.line2": "A Controlled Study of Memory in Action World Models",
    "hero.subtitle": "When the camera leaves and returns, which memory keeps the <strong>same world</strong> instead of a plausible but different scene?",
    "hero.cta.paper": "Paper",
    "hero.cta.pdf": "PDF",
    "hero.cta.ckpt": "Checkpoints",
    "hero.cta.code": "Code",
    "hero.metric.stars": "GitHub Stars",
    "hero.metric.forks": "Forks",
    "hero.note": "Controlled memory ablations on a shared <strong>Wan</strong> action-to-video stack — reproducible rows, evaluation scripts, and qualitative revisit panels.",
    "hero.authors.summary": "Authors & affiliations",
    "hero.affiliations": "HKU · Joy Future Academy, JD · CUHK · PKU · Fudan · Tsinghua · HKUST · UMich",
    "overview.kicker": "01 · Overview",
    "overview.title": "One backbone, one protocol — only memory changes.",
    "overview.lead": "Echo-Memory holds the video backbone, training recipe, and data protocol fixed, and swaps only the memory module. The goal is to separate <strong>replay fidelity</strong> from <strong>return memory</strong> when the camera leaves and comes back to the same place.",
    "overview.b1": "<strong>Shared stack</strong> — chunk-wise action-conditioned world generation on Wan.",
    "overview.b2": "<strong>Controlled variable</strong> — Context, Compression, Spatial, or State-Space memory.",
    "overview.b3": "<strong>Three probes</strong> — replay metrics, in-domain 180° loop, open-domain edited return.",
    "overview.b4": "<strong>Release</strong> — ablation scripts, GT replay, revisit assets, and paper-aligned figures.",
    "overview.fig.cap": "Controlled memory study over chunk-wise action-world generation. <span class=\"zoom-hint\">Click to expand</span>",
    "overview.fig.alt": "Echo-Memory framework overview",
    "design.kicker": "02 · Memory Design",
    "design.title": "Context · Compression · Spatial · State-Space",
    "design.lead": "All variants plug into the same write–read interface; we only change what is stored and how history is retrieved. A no-memory I2V floor re-generates from the first frame as a lower bound.",
    "design.context.title": "Context",
    "design.context.body": "Raw recent frames at K = 1, 5, or 20 chunks — tests whether longer windows alone stop drift.",
    "design.compression.title": "Compression",
    "design.compression.body": "Learned compact tokens at ratio r = 4 — history without growing raw-frame storage.",
    "design.spatial.title": "Spatial",
    "design.spatial.body": "Explicit spatial read/write state — targets layout, object pose, and viewpoint carry.",
    "design.ssm.title": "State-Space",
    "design.ssm.body": "Block-wise SSM updates — recurrent carry beyond short context windows on revisit.",
    "design.fig.cap": "Four memory families under a shared write–read interface. <span class=\"zoom-hint\">Click to expand</span>",
    "design.fig.alt": "Memory design matrix",
    "ckpt.kicker": "03 · Checkpoints",
    "ckpt.title": "Paper baselines on Hugging Face",
    "ckpt.lead": "Wan 2.1 1.3B memory rows — <strong>epoch-0</strong>, <strong>30,000 steps</strong>, static in-domain pool. Released weights: <a href=\"https://huggingface.co/Echo-Team/Echo-Memory\" target=\"_blank\" rel=\"noopener noreferrer\"><strong>Echo-Team/Echo-Memory</strong></a>",
    "ckpt.th.family": "Family",
    "ckpt.th.row": "Paper row",
    "ckpt.th.path": "HF path",
    "ckpt.th.steps": "Steps",
    "ckpt.label.download": "Download",
    "ckpt.label.eval": "In-domain eval (Echo-Memory repo)",
    "ckpt.note": "Keep the row folder in <code>CKPT</code> — <code>env/memory_baseline_runtime.py</code> infers memory flags from the path. Full index: <a href=\"https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory/blob/main/doc/checkpoints.md\" target=\"_blank\" rel=\"noopener noreferrer\">doc/checkpoints.md</a>.",
    "eval.kicker": "04 · Evaluation",
    "eval.title": "Replay · In-domain revisit · Open-domain return",
    "eval.lead": "Each branch asks a different question: Can the model reconstruct the past? Can it close a loop in-domain? After an edited first frame, does it return to the <strong>same world</strong>?",
    "eval.replay.title": "Replay",
    "eval.replay.body": "PSNR, SSIM, LPIPS on chunk-wise reconstruction — measures short-horizon pixel fidelity.",
    "eval.indomain.title": "In-domain",
    "eval.indomain.body": "180° trajectory loop closure with VLM-assisted scoring on held layouts.",
    "eval.opendomain.title": "Open-domain",
    "eval.opendomain.body": "Edited first frames and 45° return probes — stresses object identity and scene persistence.",
    "eval.dynamic.title": "Dynamic SpatialVID",
    "eval.dynamic.body": "Training and inference wrappers are public; the dynamic eval protocol is TODO.",
    "eval.fig.cap": "Replay health vs. return memory under the same stack. <span class=\"zoom-hint\">Click to expand</span>",
    "eval.fig.alt": "Three-branch evaluation summary",
    "evidence.kicker": "05 · Qualitative Evidence",
    "evidence.title": "Return probes expose identity drift.",
    "evidence.lead": "Qualitative panels follow a simple diagnostic: <strong>first frame → leave the view → revisit tail</strong>. We compare whether memory restores the same object, pose, background, and camera geometry — not merely a plausible new scene.",
    "evidence.chip1": "Memory Results",
    "evidence.chip2": "Open-Domain Sweep",
    "evidence.chip3": "Identity Anchors",
    "evidence.cap1": "Representative memory comparisons across variants. <span class=\"zoom-hint\">Click to expand</span>",
    "evidence.dynamic.note": "SpatialVID previews use one selected training scene and the same first frame, prompt, and GT camera trajectory for a 5-second first-chunk replay across all six rows.",
    "findings.kicker": "06 · Main Conclusions",
    "findings.title": "Replay quality ≠ memory quality.",
    "findings.lead": "Replay metrics and return probes do not always agree — a model can look sharp on reconstruction yet fail when the camera returns. Rankings reorder once identity under revisit is measured.",
    "findings.b1": "<strong>Raw context</strong> — more history helps open-domain return more than replay alone.",
    "findings.b2": "<strong>Compression</strong> — compact tokens can preserve replay while losing identity on return.",
    "findings.b3": "<strong>Spatial vs. SSM</strong> — explicit state and block-wise SSM trade off layout carry and long-horizon stability.",
    "findings.b4": "<strong>Takeaway</strong> — treat replay as a health check, not the final memory benchmark.",
    "findings.fig.cap": "Rank shift from replay to return — replay is not the final memory score. <span class=\"zoom-hint\">Click to expand</span>",
    "updates.kicker": "07 · News & Roadmap",
    "updates.title": "Release notes and next steps.",
    "updates.news": "News",
    "updates.roadmap": "Roadmap",
    "updates.news0": "SpatialVID support added: dynamic training/inference recipes, 5-second first-chunk replay previews, and dynamic eval marked as TODO.",
    "updates.news1": "Echo-Memory released: paper on <a href=\"https://arxiv.org/abs/2606.09803\" target=\"_blank\" rel=\"noopener noreferrer\">arXiv</a> (<a href=\"https://arxiv.org/pdf/2606.09803\" target=\"_blank\" rel=\"noopener noreferrer\">PDF</a>), project page, public code, replay/revisit eval assets, and baseline checkpoints on <a href=\"https://huggingface.co/Echo-Team/Echo-Memory\" target=\"_blank\" rel=\"noopener noreferrer\"><strong>Echo-Team/Echo-Memory</strong></a>.",
    "updates.models": "Models",
    "updates.eval": "Eval",
    "updates.rm1": "<strong>Wan 2.1 1.3B</strong> backbone and training recipes",
    "updates.rm2": "Four memory families — Context, Compression, Spatial, State-Space",
    "updates.rm3": "<strong>Dynamic training pool</strong> — SpatialVID subset export & settings",
    "updates.rm4": "<strong>Paper checkpoints</strong> — <a href=\"https://huggingface.co/Echo-Team/Echo-Memory\" target=\"_blank\" rel=\"noopener noreferrer\">Echo-Team/Echo-Memory</a>",
    "updates.rm5": "<strong>Wan 2.2</strong> + multi-scale <strong>5B / 14B</strong>",
    "updates.re1": "<strong>Dynamic eval</strong> beyond static replay/revisit",
    "updates.re2": "More revisit probes and scoring presets",
    "community.title": "Community",
    "community.lead": "Join the Echo-Memory WeChat group for release updates, checkpoint questions, and maintainer coordination.",
    "community.qr.alt": "Echo-Memory WeChat group QR code",
    "community.qr.caption": "Echo-Memory 交流群 · scan to join (QR refreshes periodically)",
    "bibtex.kicker": "08 · Citation",
    "bibtex.title": "BibTeX",
    "bibtex.lead": "Echo-Memory: A Controlled Study of Memory in Action World Models (June 2026). Licensed under <a href=\"https://creativecommons.org/licenses/by/4.0/\" target=\"_blank\" rel=\"noopener noreferrer\">CC BY 4.0</a>. Cite the arXiv preprint below.",
    "bibtex.arxiv": "arXiv",
    "bibtex.source": "Source",
    "bibtex.doi": "DOI",
    "bibtex.arxivid": "arXiv ID",
    "bibtex.pdf": "PDF",
    "bibtex.license": "License",
    "bibtex.copy": "Copy",
    "bibtex.copied": "Copied",
    "bibtex.failed": "Failed",
    "footer.copy": "© Echo Team · Joy Future Academy, JD",
    "footer.pp": "Project Page",
    "zoom.hint": "Click to expand",
    "backtop": "Back to top",
    "lightbox.close": "Close",
    "lightbox.label": "Expanded figure",
    "dev.meta.title": "Echo-Memory Developer Guide",
    "dev.meta.description": "Echo-Memory development guide — workflows, eval, and Cursor vibe coding.",
    "dev.kicker": "Development · Cursor",
    "dev.title": "Developer Guide",
    "dev.subtitle": "Hands-on coding, training, eval, and <strong>Cursor vibe coding</strong> for Echo-Memory.",
    "dev.back": "← Back to project page",
    "dev.s1.title": "1. What this guide is",
    "dev.s1.body": "<li><strong>README</strong> — paper overview, quick start, checkpoints, community.</li><li><strong>This guide</strong> — workflows, project <strong>Cursor skills</strong>, Agent tips.</li><li><strong><code>doc/</code></strong> — dataset &amp; checkpoint reference.</li><li><strong><code>.cursor/skills/</code></strong> — Agent skills for train / eval / release.</li>",
    "dev.s2.title": "2. Environment & paths",
    "dev.s2.intro": "Set these before training or eval:",
    "dev.s2.body": "<li><strong>Static in-domain pool</strong> — default root above; see <code>doc/dataset_preprocessing.md</code>.</li><li><strong>Dynamic training pool</strong> — e.g. <code>data/dynamic-memory-dataset</code>; see <code>doc/dynamic_dataset_preprocessing.md</code>.</li><li><strong>Checkpoints</strong> — <a href=\"https://huggingface.co/Echo-Team/Echo-Memory\" target=\"_blank\" rel=\"noopener noreferrer\">Echo-Team/Echo-Memory</a>; index in <code>doc/checkpoints.md</code>.</li>",
    "dev.s3.title": "3. Code map",
    "dev.s3.table": "<table class=\"dev-table\"><thead><tr><th>Path</th><th>Role</th></tr></thead><tbody><tr><td><code>.cursor/skills/</code></td><td>Cursor Agent skills (train / eval / release)</td></tr><tr><td><code>train/memory_baselines_basic/</code></td><td>Spatial / SSM / compression ablations</td></tr><tr><td><code>train/context_learning/</code></td><td>Context K=1/5/20 recipes</td></tr><tr><td><code>eval/v2/</code></td><td>Replay, loop closure, open-domain revisit</td></tr><tr><td><code>env/memory_baseline_runtime.py</code></td><td>Checkpoint → memory profile</td></tr><tr><td><code>diffsynth/</code></td><td>Wan backbone &amp; training stack</td></tr><tr><td><code>docs/</code></td><td>GitHub Pages (project + this guide)</td></tr></tbody></table>",
    "dev.s4.title": "4. Common workflows",
    "dev.s4.trainLabel": "Train one memory row (from repo root):",
    "dev.s4.evalLabel": "Smoke eval with a HF checkpoint:",
    "dev.s4.note": "Keep the row folder name in <code>CKPT</code> so runtime picks the correct memory profile.",
    "dev.s5.title": "5. Cursor vibe coding",
    "dev.s5.intro": "Use <strong>Cursor Agent</strong> (Composer) with the project skills below.",
    "dev.s5.skillsTitle": "Project skills",
    "dev.s5.skills": "<table class=\"dev-table\"><thead><tr><th>Skill</th><th>Use when</th></tr></thead><tbody><tr><td><code>echo-memory-agent</code></td><td>Scope prompts, rules, skill index</td></tr><tr><td><code>echo-memory-train</code></td><td>Memory baselines &amp; context training</td></tr><tr><td><code>echo-memory-eval</code></td><td>Replay / revisit &amp; HF quick checks</td></tr><tr><td><code>echo-memory-release</code></td><td>gh-pages, i18n, checkpoints doc</td></tr></tbody></table><p class=\"section-note\">Paths: <code>.cursor/skills/&lt;name&gt;/SKILL.md</code> — invoke in chat, e.g. <em>use echo-memory-eval to …</em></p>",
    "dev.s5.body": "<li><strong>Scope prompts</strong> — memory family, script, eval branch (<em>replay / in-domain / open-domain</em>).</li><li><strong>Entry scripts</strong> — e.g. <code>run_spatial_memory_baseline.sh</code>, <code>eval/v2/run_basic_replay_gt.sh</code>.</li><li><strong>Rules</strong> — optional <code>.cursor/rules/echo-memory.mdc</code> for pool naming &amp; public doc constraints.</li><li><strong>Ask mode</strong> — trace checkpoint mapping or read <code>diffsynth/</code> without edits.</li>",
    "dev.s5.promptLabel": "Example prompt",
    "dev.s5.prompt": "Add a quick check that downloads context_k1 from Echo-Team/Echo-Memory\nand runs eval/v2/run_basic_replay_gt.sh with the static in-domain pool.\n\nTrace env/memory_baseline_runtime.py spatial_mem → inject flags;\nsummarize in doc/checkpoints.md.",
    "dev.s5.note": "<strong>Public repo hygiene:</strong> never commit upload bash, internal benchmark names, or machine paths. WeChat QR → project page &amp; README only.",
    "dev.s6.title": "6. Site & release (maintainers)",
    "dev.s6.intro": "After editing <code>docs/index.html</code>, <code>docs/style.css</code>, or <code>docs/i18n*.js</code>:",
    "dev.s6.body": "HF weights: Hugging Face UI or <code>hf upload</code> (maintainers only). Bilingual project page: <code>docs/i18n.js</code> + <code>docs/i18n-runtime.js</code>.",
    "dev.s7.title": "7. Checklist",
    "dev.s7.l1": "Smoke eval with one HF checkpoint before tagging a release.",
    "dev.s7.l2": "Verify <code>doc/checkpoints.md</code> matches HF folder names.",
    "dev.s7.l3": "Public docs use Echo pool names — no internal paths or benchmark codenames.",
    "dev.s7.l4": "Run <code>publish_gh_pages.sh</code> after site changes; spot-check EN/中文 on the live page.",
    "dev.footer": "Repo mirror: <a href=\"https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory/blob/main/doc/DEVELOPER.md\">doc/DEVELOPER.md</a> · Community QR on <a href=\"index.html#updates\">project page</a>"
  },
  zh: {
    "meta.title": "Echo-Memory | Echo Team",
    "meta.description": "Echo-Memory：动作条件世界模型中记忆机制的对照研究。",
    "nav.home": "首页",
    "nav.overview": "概览",
    "nav.design": "设计",
    "nav.checkpoints": "权重",
    "nav.eval": "评测",
    "nav.evidence": "证据",
    "nav.findings": "结论",
    "nav.updates": "动态",
    "nav.bibtex": "引用",
    "nav.developer": "开发者手册",
    "nav.github": "GitHub",
    "nav.menu": "菜单",
    "lang.toggle": "EN",
    "lang.current": "中文",
    "lang.switch": "切换语言",
    "hero.badge": "Echo Team · Joy Future Academy, JD · 2026 年 6 月 · CC BY 4.0",
    "hero.title.line2": "动作世界模型中记忆机制的对照研究",
    "hero.subtitle": "当镜头离开再返回时，哪种记忆能让模型守住<strong>同一个世界</strong>，而不是生成一个看似合理却不同的场景？",
    "hero.cta.paper": "论文",
    "hero.cta.pdf": "PDF",
    "hero.cta.ckpt": "模型权重",
    "hero.cta.code": "代码",
    "hero.metric.stars": "GitHub Stars",
    "hero.metric.forks": "Forks",
    "hero.note": "在共享 <strong>Wan</strong> 动作到视频栈上进行可控记忆消融——可复现实验行、评测脚本与 revisit 定性面板。",
    "hero.authors.summary": "作者与单位",
    "hero.affiliations": "HKU · Joy Future Academy, JD · CUHK · PKU · Fudan · Tsinghua · HKUST · UMich",
    "overview.kicker": "01 · 概览",
    "overview.title": "同一骨干、同一协议——只换记忆模块。",
    "overview.lead": "Echo-Memory 固定视频骨干、训练配方与数据协议，仅替换记忆模块，以区分镜头离开再返回时的<strong>回放保真度</strong>与<strong>回归记忆</strong>。",
    "overview.b1": "<strong>共享栈</strong> — 基于 Wan 的分块动作条件世界生成。",
    "overview.b2": "<strong>对照变量</strong> — Context、Compression、Spatial 或 State-Space 记忆。",
    "overview.b3": "<strong>三类探针</strong> — 回放指标、域内 180° 闭环、开放域编辑后回归。",
    "overview.b4": "<strong>开源内容</strong> — 消融脚本、GT 回放、revisit 资产与论文对齐图表。",
    "overview.fig.cap": "分块动作世界生成上的可控记忆研究。<span class=\"zoom-hint\">点击放大</span>",
    "overview.fig.alt": "Echo-Memory 框架概览",
    "design.kicker": "02 · 记忆设计",
    "design.title": "Context · Compression · Spatial · State-Space",
    "design.lead": "各变体接入同一 write–read 接口，仅改变存储内容与历史检索方式。无记忆 I2V 下限仅从首帧重生成。",
    "design.context.title": "Context",
    "design.context.body": "保留 K = 1 / 5 / 20 块原始帧 — 测试更长窗口是否足以抑制漂移。",
    "design.compression.title": "Compression",
    "design.compression.body": "比率 r = 4 的紧凑 token — 在不膨胀原始帧存储的情况下保留历史。",
    "design.spatial.title": "Spatial",
    "design.spatial.body": "显式空间读写状态 — 针对布局、物体位姿与视角携带。",
    "design.ssm.title": "State-Space",
    "design.ssm.body": "Block-wise SSM 更新 — 在 revisit 上超越短上下文窗口的递归携带。",
    "design.fig.cap": "共享 write–read 接口下的四类记忆。<span class=\"zoom-hint\">点击放大</span>",
    "design.fig.alt": "记忆设计矩阵",
    "ckpt.kicker": "03 · 模型权重",
    "ckpt.title": "Hugging Face 论文 baseline",
    "ckpt.lead": "Wan 2.1 1.3B 记忆行 — <strong>epoch-0</strong>、<strong>30,000 steps</strong>、静态 in-domain 训练池。已发布权重：<a href=\"https://huggingface.co/Echo-Team/Echo-Memory\" target=\"_blank\" rel=\"noopener noreferrer\"><strong>Echo-Team/Echo-Memory</strong></a>",
    "ckpt.th.family": "家族",
    "ckpt.th.row": "论文行",
    "ckpt.th.path": "HF 路径",
    "ckpt.th.steps": "步数",
    "ckpt.label.download": "下载",
    "ckpt.label.eval": "域内评测（Echo-Memory 仓库）",
    "ckpt.note": "请在 <code>CKPT</code> 中保留行目录名 — <code>env/memory_baseline_runtime.py</code> 会从路径推断 memory 配置。完整索引：<a href=\"https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory/blob/main/doc/checkpoints.md\" target=\"_blank\" rel=\"noopener noreferrer\">doc/checkpoints.md</a>。",
    "eval.kicker": "04 · 评测",
    "eval.title": "回放 · 域内 revisit · 开放域回归",
    "eval.lead": "三个分支回答不同问题：能否重建过去？域内能否闭环？编辑首帧后能否回到<strong>同一个世界</strong>？",
    "eval.replay.title": "回放",
    "eval.replay.body": "分块重建的 PSNR / SSIM / LPIPS — 衡量短程像素保真。",
    "eval.indomain.title": "域内",
    "eval.indomain.body": "180° 轨迹闭环与 VLM 辅助评分。",
    "eval.opendomain.title": "开放域",
    "eval.opendomain.body": "编辑首帧与 45° 回归探针 — 考察物体身份与场景持续性。",
    "eval.dynamic.title": "动态 SpatialVID",
    "eval.dynamic.body": "训练和推理 wrapper 已公开；动态评测协议暂列 TODO。",
    "eval.fig.cap": "同一栈上的回放健康度 vs. 回归记忆。<span class=\"zoom-hint\">点击放大</span>",
    "eval.fig.alt": "三分支评测概览",
    "evidence.kicker": "05 · 定性证据",
    "evidence.title": "回归探针暴露身份漂移。",
    "evidence.lead": "定性面板遵循简单诊断：<strong>首帧 → 离开视角 → revisit 尾部</strong>。我们比较记忆是否恢复同一物体、位姿、背景与相机几何，而非仅生成合理的新场景。",
    "evidence.chip1": "记忆结果",
    "evidence.chip2": "开放域扫描",
    "evidence.chip3": "身份锚点",
    "evidence.cap1": "各变体的代表性记忆对比。<span class=\"zoom-hint\">点击放大</span>",
    "evidence.dynamic.note": "SpatialVID 预览来自一个精选训练场景；六组使用相同首帧、prompt 与 GT 相机轨迹做 5 秒 first-chunk replay。",
    "findings.kicker": "06 · 主要结论",
    "findings.title": "回放质量 ≠ 记忆质量。",
    "findings.lead": "回放指标与回归探针并不总一致 — 重建可以很 sharp，但镜头返回时仍可能失败。一旦测量 revisit 下的身份一致性，排名会重排。",
    "findings.b1": "<strong>原始 Context</strong> — 更长历史对开放域回归的帮助大于单纯回放。",
    "findings.b2": "<strong>Compression</strong> — 紧凑 token 可保回放但在回归时丢失身份。",
    "findings.b3": "<strong>Spatial vs. SSM</strong> — 显式状态与 block-wise SSM 在布局携带与长程稳定性间权衡。",
    "findings.b4": "<strong>要点</strong> — 将回放视为健康检查，而非最终记忆 benchmark。",
    "findings.fig.cap": "从回放到回归的排名变化 — 回放不是最终记忆分数。<span class=\"zoom-hint\">点击放大</span>",
    "updates.kicker": "07 · 新闻与路线图",
    "updates.title": "发布说明与后续计划。",
    "updates.news": "新闻",
    "updates.roadmap": "路线图",
    "updates.news0": "SpatialVID 支持已加入：动态训练/推理脚本、5 秒 first-chunk replay 预览，以及 dynamic eval TODO。",
    "updates.news1": "Echo-Memory 发布：论文上线 <a href=\"https://arxiv.org/abs/2606.09803\" target=\"_blank\" rel=\"noopener noreferrer\">arXiv</a>（<a href=\"https://arxiv.org/pdf/2606.09803\" target=\"_blank\" rel=\"noopener noreferrer\">PDF</a>），同步发布项目页、公开代码、replay/revisit 评测资产，以及 <a href=\"https://huggingface.co/Echo-Team/Echo-Memory\" target=\"_blank\" rel=\"noopener noreferrer\"><strong>Echo-Team/Echo-Memory</strong></a> baseline 权重。",
    "updates.models": "模型",
    "updates.eval": "评测",
    "updates.rm1": "<strong>Wan 2.1 1.3B</strong> 骨干与训练配方",
    "updates.rm2": "四类记忆 — Context、Compression、Spatial、State-Space",
    "updates.rm3": "<strong>Dynamic training pool</strong> — SpatialVID 子集导出与设置",
    "updates.rm4": "<strong>论文权重</strong> — <a href=\"https://huggingface.co/Echo-Team/Echo-Memory\" target=\"_blank\" rel=\"noopener noreferrer\">Echo-Team/Echo-Memory</a>",
    "updates.rm5": "<strong>Wan 2.2</strong> + 多尺度 <strong>5B / 14B</strong>",
    "updates.re1": "静态 replay/revisit 之外的 <strong>动态评测</strong>",
    "updates.re2": "更多 revisit 探针与评分预设",
    "community.title": "社区交流",
    "community.lead": "扫码加入 Echo-Memory 微信群，获取发布更新、权重使用与维护协调信息。",
    "community.qr.alt": "Echo-Memory 微信群二维码",
    "community.qr.caption": "Echo-Memory 交流群 · 扫码加入（二维码会定期更新）",
    "bibtex.kicker": "08 · 引用",
    "bibtex.title": "BibTeX",
    "bibtex.lead": "Echo-Memory: A Controlled Study of Memory in Action World Models（2026 年 6 月）。许可：<a href=\"https://creativecommons.org/licenses/by/4.0/\" target=\"_blank\" rel=\"noopener noreferrer\">CC BY 4.0</a>。请使用下方 arXiv BibTeX 引用。",
    "bibtex.arxiv": "arXiv",
    "bibtex.source": "来源",
    "bibtex.doi": "DOI",
    "bibtex.arxivid": "arXiv ID",
    "bibtex.pdf": "PDF",
    "bibtex.license": "许可",
    "bibtex.copy": "复制",
    "bibtex.copied": "已复制",
    "bibtex.failed": "失败",
    "footer.copy": "© Echo Team · Joy Future Academy, JD",
    "footer.pp": "项目页",
    "zoom.hint": "点击放大",
    "backtop": "回到顶部",
    "lightbox.close": "关闭",
    "lightbox.label": "放大图表",
    "dev.meta.title": "Echo-Memory 开发者指南",
    "dev.meta.description": "Echo-Memory 开发指南 — 工作流、评测与 Cursor 协作编程。",
    "dev.kicker": "开发 · Cursor",
    "dev.title": "开发者指南",
    "dev.subtitle": "Echo-Memory 实战开发、训练评测与 <strong>Cursor 协作编程</strong>。",
    "dev.back": "← 返回项目页",
    "dev.s1.title": "1. 本指南定位",
    "dev.s1.body": "<li><strong>README</strong> — 论文概览、快速上手、权重、社区。</li><li><strong>本页</strong> — 工作流、项目 <strong>Cursor skills</strong>、Agent 技巧。</li><li><strong><code>doc/</code></strong> — 数据集与权重参考。</li><li><strong><code>.cursor/skills/</code></strong> — 训练 / 评测 / 发布类 Agent 技能。</li>",
    "dev.s2.title": "2. 环境与路径",
    "dev.s2.intro": "训练或评测前设置：",
    "dev.s2.body": "<li><strong>Static in-domain pool</strong> — 默认路径见上；详见 <code>doc/dataset_preprocessing.md</code>。</li><li><strong>Dynamic training pool</strong> — 如 <code>data/dynamic-memory-dataset</code>；详见 <code>doc/dynamic_dataset_preprocessing.md</code>。</li><li><strong>权重</strong> — <a href=\"https://huggingface.co/Echo-Team/Echo-Memory\" target=\"_blank\" rel=\"noopener noreferrer\">Echo-Team/Echo-Memory</a>；索引见 <code>doc/checkpoints.md</code>。</li>",
    "dev.s3.title": "3. 代码地图",
    "dev.s3.table": "<table class=\"dev-table\"><thead><tr><th>路径</th><th>作用</th></tr></thead><tbody><tr><td><code>.cursor/skills/</code></td><td>Cursor Agent 技能（训练 / 评测 / 发布）</td></tr><tr><td><code>train/memory_baselines_basic/</code></td><td>Spatial / SSM / 压缩消融</td></tr><tr><td><code>train/context_learning/</code></td><td>Context K=1/5/20 配方</td></tr><tr><td><code>eval/v2/</code></td><td>回放、闭环、开放域 revisit</td></tr><tr><td><code>env/memory_baseline_runtime.py</code></td><td>权重 → 记忆配置</td></tr><tr><td><code>diffsynth/</code></td><td>Wan 骨干与训练栈</td></tr><tr><td><code>docs/</code></td><td>GitHub Pages（项目页 + 本指南）</td></tr></tbody></table>",
    "dev.s4.title": "4. 常用工作流",
    "dev.s4.trainLabel": "训练一条 memory 行（仓库根目录）：",
    "dev.s4.evalLabel": "用 HF 权重做 quick eval：",
    "dev.s4.note": "<code>CKPT</code> 路径需保留行目录名，以便 runtime 匹配记忆配置。",
    "dev.s5.title": "5. Cursor 协作编程",
    "dev.s5.intro": "使用 <strong>Cursor Agent</strong>（Composer）配合下方项目 skills。",
    "dev.s5.skillsTitle": "项目 Skills",
    "dev.s5.skills": "<table class=\"dev-table\"><thead><tr><th>Skill</th><th>适用场景</th></tr></thead><tbody><tr><td><code>echo-memory-agent</code></td><td>Prompt 范围、Rules、技能索引</td></tr><tr><td><code>echo-memory-train</code></td><td>Memory baseline 与 Context 训练</td></tr><tr><td><code>echo-memory-eval</code></td><td>回放 / revisit 与 HF quick check</td></tr><tr><td><code>echo-memory-release</code></td><td>gh-pages、i18n、权重文档</td></tr></tbody></table><p class=\"section-note\">路径：<code>.cursor/skills/&lt;name&gt;/SKILL.md</code> — 在对话中引用，如 <em>use echo-memory-eval 来 …</em></p>",
    "dev.s5.body": "<li><strong>明确范围</strong> — memory 家族、脚本、评测分支（<em>replay / in-domain / open-domain</em>）。</li><li><strong>入口脚本</strong> — 如 <code>run_spatial_memory_baseline.sh</code>、<code>eval/v2/run_basic_replay_gt.sh</code>。</li><li><strong>Rules</strong> — 可选 <code>.cursor/rules/echo-memory.mdc</code> 约束池命名与公开文档。</li><li><strong>Ask 模式</strong> — 追踪 checkpoint 映射或阅读 <code>diffsynth/</code>，不改代码。</li>",
    "dev.s5.promptLabel": "示例 Prompt",
    "dev.s5.prompt": "添加 quick check：从 Echo-Team/Echo-Memory 下载 context_k1，\n用 static in-domain pool 跑 eval/v2/run_basic_replay_gt.sh。\n\n追踪 env/memory_baseline_runtime.py 如何把 spatial_mem\n权重映射到 inject 标志，并在 doc/checkpoints.md 摘要说明。",
    "dev.s5.note": "<strong>公开仓库规范：</strong> 勿提交上传脚本、内部 benchmark 名、本机路径。微信群二维码仅在项目页与 README。",
    "dev.s6.title": "6. 站点与发布（维护者）",
    "dev.s6.intro": "修改 <code>docs/index.html</code>、<code>docs/style.css</code> 或 <code>docs/i18n*.js</code> 后：",
    "dev.s6.body": "HF 权重：网页或 <code>hf upload</code> 更新（仅维护者）。项目页双语：<code>docs/i18n.js</code> + <code>docs/i18n-runtime.js</code>。",
    "dev.s7.title": "7. 检查清单",
    "dev.s7.l1": "发版前用至少一个 HF 权重跑 quick eval。",
    "dev.s7.l2": "确认 <code>doc/checkpoints.md</code> 与 HF 目录名一致。",
    "dev.s7.l3": "公开文档使用 Echo 池命名 — 无内部路径或 benchmark 代号。",
    "dev.s7.l4": "改站点后运行 <code>publish_gh_pages.sh</code>，检查线上 EN/中文 切换。",
    "dev.footer": "仓库副本：<a href=\"https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory/blob/main/doc/DEVELOPER.md\">doc/DEVELOPER.md</a> · 社区二维码见 <a href=\"index.html#updates\">项目页</a>"
  }
};