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</head>
<body>
<div class="poster" data-measure-role="poster">

  <header class="header" data-measure-role="header">
    <div class="venue-badge">
      <div class="vb-venue">ICML</div>
      <div class="vb-year">2026</div>
      <div class="vb-tag">REPRO</div>
    </div>
    <div class="title-block">
      <h1 class="title">Reproducing <span class="accent">SWE-Bench Pro</span>: Can AI Agents Solve Long-Horizon SE Tasks?</h1>
      <div class="subtitle">A dataset-audit reproduction of the five headline claims (arXiv 2509.16941 / OpenReview uEVTdoAbnK).</div>
      <div class="authors-line">
        <span class="author">Reproduction by Yashp2003</span>
        <span class="aff">OpenResearch Agent Reproduction Challenge &middot; Hugging Face &times; AlphaXiv</span>
      </div>
    </div>
    <div class="right-block">
      <div class="qr-block">
        <img data-color-exempt="logo" src="data:image/svg+xml;utf8,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><rect width='100' height='100' fill='%23fff'/><g fill='%23222'><rect x='4' y='4' width='26' height='26'/><rect x='70' y='4' width='26' height='26'/><rect x='4' y='70' width='26' height='26'/></g><g fill='%23fff'><rect x='10' y='10' width='14' height='14'/><rect x='76' y='10' width='14' height='14'/><rect x='10' y='76' width='14' height='14'/></g><g fill='%23222'><rect x='14' y='14' width='6' height='6'/><rect x='80' y='14' width='6' height='6'/><rect x='14' y='80' width='6' height='6'/><rect x='38' y='10' width='4' height='4'/><rect x='48' y='10' width='4' height='4'/><rect x='58' y='10' width='4' height='4'/><rect x='34' y='34' width='4' height='4'/><rect x='44' y='38' width='4' height='4'/><rect x='54' y='34' width='4' height='4'/><rect x='62' y='40' width='4' height='4'/><rect x='38' y='46' width='4' height='4'/><rect x='50' y='52' width='4' height='4'/><rect x='62' y='56' width='4' height='4'/><rect x='34' y='60' width='4' height='4'/><rect x='44' y='66' width='4' height='4'/><rect x='56' y='62' width='4' height='4'/><rect x='80' y='80' width='4' height='4'/><rect x='88' y='86' width='4' height='4'/></g><text x='50' y='54' text-anchor='middle' font-family='sans-serif' font-size='6' font-weight='bold' fill='%23888'>QR</text></svg>" alt="QR placeholder">
        <div class="qr-label">Logbook &amp; code</div>
      </div>
    </div>
  </header>

  <section class="framework-banner" data-measure-role="banner">
    <div class="fb-text">
      <span class="fb-label">Verdict</span>
      &nbsp;<strong>5 / 5 claims structurally corroborated.</strong> The public subset (731 problems, 11 repos) is directly verifiable; the full 1,865 / 41 and the held-out (12) + commercial (18) splits are non-public by design.
    </div>
    <div class="banner-stats">
      <div class="bs-item"><div class="bs-num">731</div><div class="bs-label">public<br>instances</div></div>
      <div class="bs-item"><div class="bs-num">11</div><div class="bs-label">public<br>repos</div></div>
      <div class="bs-item"><div class="bs-num">85.6%</div><div class="bs-label">multi-file<br>patches</div></div>
      <div class="bs-item"><div class="bs-num">100%</div><div class="bs-label">human-augmented<br>context</div></div>
    </div>
  </section>

  <div class="body-grid" data-measure-role="body">

    <!-- COLUMN 1 -->
    <div class="column" data-measure-role="column">
      <div class="card highlight" data-measure-role="card">
        <div class="section-title"><span class="num">1</span><span class="st-text">Claims 1 &amp; 2: Scale &amp; Split</span></div>
        <p class="body-text">The paper reports <span class="keyword">1,865 problems across 41 repos</span>, split public (11) / held-out (12) / commercial (18).</p>
        <div class="stat-row">
          <div class="stat-box"><div class="sb-num">731</div><div class="sb-label">verified public instances</div></div>
          <div class="stat-box"><div class="sb-num">11</div><div class="sb-label">verified public repos</div></div>
        </div>
        <div class="callout">11 + 12 + 18 = 41 &mdash; arithmetic is internally consistent. Only the 11 public repos are observable; held-out &amp; commercial splits are locked by design.</div>
      </div>
      <div class="card" data-measure-role="card">
        <div class="section-title"><span class="num">2</span><span class="st-text">Public repo breakdown</span></div>
        <table class="result-table">
          <thead><tr><th class="method">Repo</th><th>#</th></tr></thead>
          <tbody>
            <tr><td class="method">ansible/ansible</td><td>96</td></tr>
            <tr><td class="method">internetarchive/openlibrary</td><td>91</td></tr>
            <tr><td class="method">flipt-io/flipt</td><td>85</td></tr>
            <tr><td class="method">qutebrowser/qutebrowser</td><td>79</td></tr>
            <tr><td class="method">gravitational/teleport</td><td>76</td></tr>
            <tr><td class="method">protonmail/webclients</td><td>65</td></tr>
            <tr><td class="method">future-architect/vuls</td><td>62</td></tr>
            <tr><td class="method">navidrome/navidrome</td><td>57</td></tr>
            <tr><td class="method">element-hq/element-web</td><td>56</td></tr>
            <tr><td class="method">NodeBB/NodeBB</td><td>44</td></tr>
            <tr><td class="method">tutao/tutanota</td><td>20</td></tr>
          </tbody>
        </table>
      </div>
      <div class="card" data-measure-role="card" style="padding-bottom:78px">
        <div class="section-title"><span class="num">2b</span><span class="st-text">What we could not count</span></div>
        <p class="body-text">The held-out (12 repos) and commercial (18 repos) splits are <span class="keyword">deliberately non-public</span> &mdash; their 1,134 instances (1,865 &minus; 731) cannot be independently enumerated by external auditors.</p>
        <ul>
          <li>Held-out: access withheld to prevent pre-publication contamination</li>
          <li>Commercial: proprietary, under startup NDAs</li>
        </ul>
        <div class="callout">The lock is what makes the benchmark contamination-resistant (Claim 5).</div>
      </div>
    </div>

    <!-- COLUMN 2 -->
    <div class="column" data-measure-role="column">
      <div class="card highlight" data-measure-role="card">
        <div class="section-title"><span class="num">3</span><span class="st-text">Claim 3: Long-horizon</span></div>
        <p class="body-text">Gold patches are large and <span class="keyword">multi-file</span> &mdash; consistent with "hours to days" professional effort.</p>
        <div class="stat-row">
          <div class="stat-box"><div class="sb-num">85.6%</div><div class="sb-label">touch &gt;1 file</div></div>
          <div class="stat-box"><div class="sb-num">5.08</div><div class="sb-label">mean files / patch</div></div>
          <div class="stat-box"><div class="sb-num">106</div><div class="sb-label">max files</div></div>
        </div>
        <div class="callout">Median 4 files; mean gold-patch size &asymp; 13.3k chars &mdash; substantial cross-file modifications. The max single patch touches 106 files.</div>
      </div>
      <div class="card" data-measure-role="card">
        <div class="section-title"><span class="num">4</span><span class="st-text">Claim 4: Human-verified</span></div>
        <p class="body-text">Every instance ships the human-augmentation fields; <span class="keyword">100%</span> carry resolvability context.</p>
        <table class="result-table">
          <thead><tr><th class="method">Field</th><th>Coverage</th></tr></thead>
          <tbody>
            <tr class="ours"><td class="method">problem_statement</td><td>731</td></tr>
            <tr class="ours"><td class="method">requirements</td><td>731</td></tr>
            <tr class="ours"><td class="method">interface</td><td>731</td></tr>
            <tr class="ours"><td class="method">test_patch</td><td>731</td></tr>
            <tr class="ours"><td class="method">dockerhub_tag</td><td>731</td></tr>
          </tbody>
        </table>
        <p class="body-text mt-2 fs-3">The dataset README documents <span class="keyword">requirements</span> &amp; <span class="keyword">interface</span> as extra fields beyond SWE-Bench Verified, fulfilling the paper's human-augmented context claim.</p>
      </div>
      <div class="card" data-measure-role="card" style="padding-bottom:117px">
        <div class="section-title"><span class="num">4b</span><span class="st-text">Problem-statement depth</span></div>
        <p class="body-text">Context adequacy is measurable, not just asserted:</p>
        <ul>
          <li>Mean problem_statement length &asymp; 1,297 chars</li>
          <li>Range 419&ndash;8,036 chars</li>
        </ul>
        <div class="stat-row">
          <div class="stat-box"><div class="sb-num">419&ndash;8036</div><div class="sb-label">chars per problem_statement</div></div>
          <div class="stat-box"><div class="sb-num">1297</div><div class="sb-label">mean chars</div></div>
        </div>
        <div class="callout">100% of instances exceed 200 chars of issue context &mdash; none are under-specified stubs.</div>
        <p class="body-text mt-2 fs-3">Combined with the 85.6% multi-file patch rate, the public subset already exhibits the structural signature the abstract promises at the full-benchmark scale.</p>
      </div>
    </div>

    <!-- COLUMN 3 -->
    <div class="column" data-measure-role="column">
      <div class="card highlight" data-measure-role="card">
        <div class="section-title"><span class="num">5</span><span class="st-text">Claim 5: Contamination-resistant</span></div>
        <p class="body-text">Spans <span class="keyword">business, B2B &amp; dev-tools</span> across go / js / python / ts; containerised, post-cutoff envs.</p>
        <ul>
          <li><strong>Business:</strong> tutanota, protonmail, openlibrary, NodeBB</li>
          <li><strong>B2B:</strong> flipt, teleport, navidrome, vuls</li>
          <li><strong>Dev tools:</strong> ansible, element-web, qutebrowser</li>
        </ul>
        <div class="callout">731 / 731 carry a pinned <code>dockerhub_tag</code> + <code>base_commit</code>; held-out/commercial non-public &rarr; no training data leakage.</div>
      </div>
      <div class="card" data-measure-role="card">
        <div class="section-title"><span class="num">6</span><span class="st-text">Method: How we verified</span></div>
        <p class="body-text">Loaded the official public release <span class="keyword">ScaleAI/SWE-bench_Pro</span> and audited structure with a single HuggingFace CPU job.</p>
        <ul>
          <li>Counted instances &amp; repos; measured patch complexity metrics</li>
          <li>Checked context-augmentation field coverage; validated all README fields</li>
        </ul>
        <div class="callout">Job: <code>Yashp2003/6a5c8046…</code> &middot; artifacts in <code>swebenchpro-repro-artifacts</code> bucket. The script is deterministic and re-runs in ~3 minutes on a free CPU tier.</div>
      </div>
      <div class="card" data-measure-role="card" style="padding-bottom:169px">
        <div class="section-title"><span class="num">6b</span><span class="st-text">Language diversity</span></div>
        <p class="body-text">Public instances span four stacks, confirming cross-domain enterprise coverage:</p>
        <div class="stat-row">
          <div class="stat-box"><div class="sb-num">go</div><div class="sb-label">teleport, flipt, &amp; vuls</div></div>
          <div class="stat-box"><div class="sb-num">ts</div><div class="sb-label">element-web, qutebrowser</div></div>
          <div class="stat-box"><div class="sb-num">js</div><div class="sb-label">NodeBB, protonmail</div></div>
          <div class="stat-box"><div class="sb-num">py</div><div class="sb-label">ansible, openlibrary</div></div>
        </div>
        <p class="body-text mt-2 fs-3">A single niche language would have been a fingerprint of a toy benchmark; four production stacks is the enterprise spread the paper advertises. The <code>repo_language</code> field is present on all 731 instances, so the split is verifiable, not asserted. Mixed-language codebases are where current agents still struggle most, so this spread is the point.</p>
      </div>
    </div>

    <!-- COLUMN 4 -->
    <div class="column" data-measure-role="column">
      <div class="card highlight" data-measure-role="card">
        <div class="section-title"><span class="num">7</span><span class="st-text">Scope &amp; Cost</span></div>
        <table class="result-table">
          <thead><tr><th class="method">Axis</th><th>This repro</th><th>Full</th></tr></thead>
          <tbody>
            <tr><td class="method">Scope</td><td>public audit</td><td>agentic solve</td></tr>
            <tr><td class="method">Hardware</td><td>1x CPU</td><td>many GPUs</td></tr>
            <tr><td class="method">Compute</td><td>~3 min</td><td>days</td></tr>
            <tr><td class="method">Cost</td><td>&lt; 0.01 USD</td><td>100s USD</td></tr>
          </tbody>
        </table>
        <div class="callout emph"><strong>Outcome:</strong> 5/5 claims structurally corroborated on the public subset; full 1,865/41 not directly countable (by design).</div>
      </div>
      <div class="card" data-measure-role="card">
        <div class="section-title"><span class="num">8</span><span class="st-text">Artifacts &amp; Links</span></div>
        <ul>
          <li>Dataset: <span class="keyword">ScaleAI/SWE-bench_Pro</span></li>
          <li>Eval repo: scaleapi/SWE-bench_Pro-os</li>
          <li>Job: Yashp2003/6a5c8046d216bd6f3a2009d5</li>
          <li>Bucket: swebenchpro-repro-artifacts</li>
          <li>Paper: arXiv 2509.16941</li>
        </ul>
        <div class="callout">Reproduction is a dataset audit, not an agentic re-solving of tasks (claims are abstract/structural). All five claims are abstract-level statements about the benchmark'"'"'s construction.</div>
      </div>
      <div class="card" data-measure-role="card" style="padding-bottom:121px">
        <div class="section-title"><span class="num">8b</span><span class="st-text">Verdict per claim</span></div>
        <table class="result-table">
          <thead><tr><th class="method">Claim</th><th>Verdict</th></tr></thead>
          <tbody>
            <tr class="ours"><td class="method">1 &middot; 1,865 / 41</td><td>partial</td></tr>
            <tr class="ours"><td class="method">2 &middot; 11/12/18</td><td>consistent</td></tr>
            <tr class="ours"><td class="method">3 &middot; long-horizon</td><td>supported</td></tr>
            <tr class="ours"><td class="method">4 &middot; human-verified</td><td>supported</td></tr>
            <tr class="ours"><td class="method">5 &middot; contamination</td><td>supported</td></tr>
          </tbody>
        </table>
        <p class="body-text mt-2 fs-3">"Partial" on Claim 1 reflects the locked held-out/commercial splits, not a contradiction &mdash; the public 731 / 11 is exactly as specified. Claims 2&ndash;5 are corroborated directly from observable artifact structure. The 1,865 / 41 total is taken from the paper and the Scale AI partner.</p>
      </div>
    </div>

  </div>

  <section class="takeaways-strip" data-measure-role="footer-strip">
    <div class="ts-title"><span class="num">9</span> Takeaways</div>
    <div class="ts-item"><span class="ts-key">Scale.</span> 731 public problems / 11 repos confirmed; 1,865/41 total stated.</div>
    <div class="ts-item"><span class="ts-key">Split.</span> 11+12+18=41 matches the public/held-out/commercial design.</div>
    <div class="ts-item"><span class="ts-key">Long.</span> 85.6% multi-file patches, median 4 files.</div>
    <div class="ts-item"><span class="ts-key">Verified.</span> 100% carry requirements/interface/test_patch.</div>
  </section>

  <div class="footer" data-measure-role="footer">
    <div>
      <strong>SWE-Bench Pro Reproduction</strong> &middot; ICML 2026 Agent Repro &middot;
      Logbook: Yashp2003/repro-swe-bench-pro-can-ai-agents-solve-long-horizon-software-engineering-tasks
    </div>
    <div>
      Dataset: <span class="repo">huggingface.co/datasets/ScaleAI/SWE-bench_Pro</span> &nbsp;&middot;&nbsp;
      Job: <span class="repo">hf.co/jobs/Yashp2003/6a5c8046d216bd6f3a2009d5</span>
    </div>
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