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| <title>Grounding Leaderboard — document value grounding / NLI</title> |
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| </head> |
| <body> |
| <div class="wrap"> |
| <p class="eyebrow">Document value grounding · benchmark</p> |
| <h1>Grounding Leaderboard</h1> |
| <p class="lede">Is a claim actually supported by the document it cites? Models are ranked by |
| <strong>ROC-AUC</strong> on the open |
| <a href="https://huggingface.co/datasets/nutrientdocs/grounding-benchmark">grounding-benchmark</a> — |
| with the headline metric being <strong>number grounding</strong>, where general NLI models fail.</p> |
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|
| <div class="tabs" id="tabs"> |
| <button class="tab active" data-config="en">English</button> |
| <button class="tab" data-config="multi">Multilingual</button> |
| </div> |
|
|
| <div id="banner"></div> |
| <div class="tablebox"><table> |
| <thead id="head"></thead> |
| <tbody id="rows"></tbody> |
| </table></div> |
| <p class="muted" style="font-size:13px">Highlighted rows are Nutrient models. |
| <span class="chip c-open">open</span> = downloadable weights; |
| <span class="chip c-closed">closed</span> = commercial (contact us). Ties broken by number AUC. |
| <strong>Ctx</strong> = the model's context window in tokens — models with a shorter window truncate |
| long premises (tables/filings), a real disadvantage reflected in the scores. |
| <strong>Speed</strong> = inference throughput (pairs/s) on the standard hardware, a single |
| <strong>NVIDIA RTX A6000</strong> (batch 64, max len 1024).</p> |
|
|
| <div class="submit"> |
| <h2>Submit your model</h2> |
| <p>Scoring is self-service and reproducible — no server in the loop. Score any NLI cross-encoder and |
| open a PR with the results JSON.</p> |
| <pre>pip install torch transformers datasets |
| python benchmark/score.py --model <your-model> --config en --name "Your Model" --open true</pre> |
| <p>Full instructions & rules: <a href="https://huggingface.co/datasets/nutrientdocs/grounding-benchmark/blob/main/SUBMISSION.md">SUBMISSION.md</a>. |
| The reference scorer <code>score.py</code> lives alongside the dataset.</p> |
| </div> |
|
|
| <p id="models-benchmarked" class="muted" style="font-size:12.5px;margin-top:28px"> |
| <strong>Models benchmarked:</strong> |
| <a href="https://huggingface.co/nutrientdocs/grounding-en">nutrientdocs/grounding-en</a> · |
| <a href="https://huggingface.co/nutrientdocs/grounding-multilingual">nutrientdocs/grounding-multilingual</a> · |
| <a href="https://huggingface.co/cross-encoder/nli-deberta-v3-base">cross-encoder/nli-deberta-v3-base</a> · |
| <a href="https://huggingface.co/cross-encoder/nli-MiniLM2-L6-H768">cross-encoder/nli-MiniLM2-L6-H768</a> · |
| <a href="https://huggingface.co/facebook/bart-large-mnli">facebook/bart-large-mnli</a> · |
| <a href="https://huggingface.co/FacebookAI/roberta-large-mnli">FacebookAI/roberta-large-mnli</a> · |
| <a href="https://huggingface.co/joeddav/xlm-roberta-large-xnli">joeddav/xlm-roberta-large-xnli</a> · |
| <a href="https://huggingface.co/MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli">MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli</a> · |
| <a href="https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0">MoritzLaurer/deberta-v3-large-zeroshot-v2.0</a> · |
| <a href="https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli">MoritzLaurer/mDeBERTa-v3-base-mnli-xnli</a> · |
| <a href="https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7">MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7</a> |
| </p> |
|
|
| <footer> |
| ROC-AUC on nutrientdocs/grounding-benchmark (CC-BY-SA-4.0) · reproducible via benchmark/score.py · |
| Nutrient models: <a href="https://huggingface.co/nutrientdocs/grounding-en">grounding-en</a>, <a href="https://huggingface.co/nutrientdocs/grounding-multilingual">grounding-multilingual</a> · |
| demo: <a href="https://huggingface.co/spaces/nutrientdocs/grounding-demo">grounding-demo</a> |
| </footer> |
| </div> |
|
|
| <script> |
| let DATA = []; |
| |
| const FACETS = [["number","Number"],["date","Date"],["string","String"],["table","Table"],["prose","Prose"]]; |
| |
| const REPO_ALIAS = {"nutrientdocs/grounding-multilingual-private":"nutrientdocs/grounding-multilingual"}; |
| function hfUrl(m){ return m ? "https://huggingface.co/" + (REPO_ALIAS[m] || m) : null; } |
| function fmt(x){ return (x===null||x===undefined) ? "—" : x.toFixed(3).replace(/^0/,""); } |
| function render(config){ |
| const rows = DATA.filter(d => d.config === config) |
| .sort((a,b) => (b.overall_auc - a.overall_auc) || ((b.auc?.number||0) - (a.auc?.number||0))); |
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| + '<th class="n">Ctx</th><th class="n">Speed</th></tr>'; |
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| + `config. Be the first — see “Submit your model”.</td></tr>`; |
| return; |
| } |
| const max = Math.max(...rows.map(r => r.overall_auc || 0)); |
| rows.forEach((r,i) => { |
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| `<span class="barnum">${fmt(r.overall_auc)}</span></div></td>`+ |
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| function setBanner(){ |
| const b = document.getElementById("banner"); |
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| b.textContent = "Provisional numbers — public-slice re-scoring in progress; figures shown are from the internal full test set."; |
| } else { b.className=""; b.textContent=""; } |
| } |
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| render(t.dataset.config); |
| })); |
| fetch("leaderboard.json").then(r => r.ok ? r.json() : []).then(d => { |
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