Filter benchmark browser by scored model

site/assets/app.js

@@ -374,6 +374,11 @@ const I18N = {
     "Shown / corpus": "显示数／目录总数",
     "source document": "份来源文档",
     "Document publication date": "文档发布日期",
+    "Model release": "模型发布日期",
+    "Document published": "文档发布日期",
+    "Model with a reported score": "已有报告成绩的模型",
+    "Filter by model, e.g. GPT-6 Sol": "按模型筛选，例如 GPT-6 Sol",
+    "Searching all benchmarks (score cutoff paused)": "搜索全部 benchmark（暂不按分数筛选）",
     "Reporting organization color key": "报告机构颜色图例",
     "Distinct cited documents, including model reports and registry pages": "按引用的独立文档去重，包括模型报告和登记页面",
     "Each source document counts once per benchmark record.": "每份来源文档对同一条 benchmark 记录只计一次。",
@@ -1228,6 +1233,7 @@ const state = {
   // arrived, so "not yet loaded" and "failed to load" must not look alike.
   benchmarkIndexLoaded: false,
   benchmarkQuery: "",
+  benchmarkModel: "",
   leaderboardShowAll: false,
   leaderboardTopExpanded: false,
   todayResultsKey: "",
@@ -1466,6 +1472,7 @@ function readUrl() {
   state.lheight = ["cards", "documents"].includes(params.get("lheight")) ? "documents" : "models";
   state.benchmarkVisibleLimit = BENCHMARK_SEARCH_LIMIT;
   state.benchmarkQuery = (params.get("bq") || "").trim();
+  state.benchmarkModel = (params.get("bmodel") || "").trim();
   state.lfrontier = params.get("lfrontier") || "";
   state.lfrontierExplicit = Boolean(state.lfrontier);
   // Existing benchmark permalinks follow the score history to its new tab.
@@ -1549,6 +1556,7 @@ function writeUrl(mode = "replace") {
   if (!utility && state.view === "saturation") {
     params.set("lscore", state.lscore);
     if (state.benchmarkQuery) params.set("bq", state.benchmarkQuery);
+    if (state.benchmarkModel) params.set("bmodel", state.benchmarkModel);
     // A benchmark auto-picked as the default is not the reader's choice, so it
     // stays out of the URL until they select one themselves.
     if (state.lfrontierExplicit && state.lfrontier) {
@@ -4704,8 +4712,22 @@ function saturationRows() {
   const matches = benchmarkQueryIds();
   // Search is a lookup across the whole catalog. It temporarily bypasses the
   // browsing cutoff without changing the shared slider value.
-  const rows = scoreBrowseRows(matches ? 100 : state.lscore);
-  return matches ? rows.filter((row) => matches.has(row.id)) : rows;
+  const rows = scoreBrowseRows(matches || state.benchmarkModel ? 100 : state.lscore);
+  const named = matches ? rows.filter((row) => matches.has(row.id)) : rows;
+  if (!state.benchmarkModel) return named;
+  const needle = foldName(state.benchmarkModel);
+  if (!needle) return [];
+  const index = new Map((state.benchmarkIndex || []).map((record) => [record.slug, record]));
+  return named.filter((row) => (index.get(row.id)?.scored_models || [])
+    .some((model) => foldName(model.name).includes(needle)))
+    .sort((a, b) => (latestMatchingModel(index.get(b.id), needle)?.date || "")
+      .localeCompare(latestMatchingModel(index.get(a.id), needle)?.date || "") || a.name.localeCompare(b.name));
+}
+
+function latestMatchingModel(record, needle) {
+  return (record?.scored_models || [])
+    .filter((model) => foldName(model.name).includes(needle))
+    .sort((a, b) => (b.date || "").localeCompare(a.date || ""))[0];
 }
 
 function scoreRankingRows() {
@@ -4722,6 +4744,9 @@ function scoreSummaryLabel(summary) {
 }
 
 function scoreBrowseResultRow(row) {
+  const record = (state.benchmarkIndex || []).find((item) => item.slug === row.id);
+  const needle = foldName(state.benchmarkModel);
+  const matchedModel = needle ? latestMatchingModel(record, needle) : null;
   const button = element("button", {
     className: "benchmark-result score-browse-result",
     attrs: { type: "button", "aria-pressed": row.id === state.lfrontier ? "true" : "false" },
@@ -4730,6 +4755,7 @@ function scoreBrowseResultRow(row) {
     element("span", { className: "benchmark-result-facts", text: [scoreSourceLabel(row.source),
       row.date ? `${t(benchmarkDateLabel(row))} ${formatDate(row.date, { dateStyle: "medium" })}` : t("Date unknown"),
       matchesScoreCutoff(row.summary, 100) ? "" : t("No score reported"),
+      matchedModel ? `${matchedModel.name}${matchedModel.date ? ` · ${t(matchedModel.date_precision === "model_announcement" ? "Model release" : "Document published")} ${formatDate(matchedModel.date, { dateStyle: "medium" })}` : ""}` : "",
     ].filter(Boolean).join(" · ") }),
   ]);
   button.addEventListener("click", () => {
@@ -4814,6 +4840,7 @@ function renderBenchmarkSearch() {
   const status = byId("benchmark-search-status");
   if (!container || !status || !state.data) return;
   byId("benchmark-search-input").value = state.benchmarkQuery;
+  byId("benchmark-model-input").value = state.benchmarkModel;
   const rows = saturationRows();
   const shown = rows.slice(0, state.benchmarkVisibleLimit);
   replaceChildren(container, shown.map(scoreBrowseResultRow));
@@ -4824,11 +4851,11 @@ function renderBenchmarkSearch() {
   status.textContent = [t("{shown} of {total} matches")
     .replace("{shown}", shown.length.toLocaleString())
     .replace("{total}", rows.length.toLocaleString()),
-    state.benchmarkQuery ? t("Searching all benchmarks (filters paused)") : "", coverage].filter(Boolean).join(" · ");
+    state.benchmarkQuery || state.benchmarkModel ? t("Searching all benchmarks (score cutoff paused)") : "", coverage].filter(Boolean).join(" · ");
   if (!rows.length) {
     container.append(element("p", { className: "empty-state", text: loading
       ? t("Loading benchmark details…") : t("No benchmarks match these filters.") }));
-    if (!state.benchmarkQuery && state.lscore < 100) {
+    if (!state.benchmarkQuery && !state.benchmarkModel && state.lscore < 100) {
       const all = element("button", { className: "clear-button", text: t("All"), attrs: { type: "button" } });
       all.addEventListener("click", () => setScoreFilter(100));
       container.append(all);
@@ -5266,6 +5293,13 @@ function initBenchmarkSearch() {
     writeUrl();
   });
   input.addEventListener("input", onInput);
+  const modelInput = byId("benchmark-model-input");
+  modelInput.addEventListener("input", debounce(() => {
+    state.benchmarkModel = modelInput.value.trim();
+    state.benchmarkVisibleLimit = BENCHMARK_SEARCH_LIMIT;
+    renderSaturation();
+    writeUrl();
+  }));
   loadBenchmarkIndex().then((records) => {
     // Loading and failure remain explicit; no source-specific fallback corpus.
     state.benchmarkIndex = records;

site/assets/styles.css

@@ -2795,6 +2795,14 @@ td a {
   font-size: 0.78rem;
 }
 
+.benchmark-model-label {
+  display: block;
+  margin: 0.85rem 0 0.4rem;
+  font-family: var(--utility);
+  font-size: 0.78rem;
+  font-weight: 700;
+}
+
 .benchmark-navigator p:not(.eyebrow):not(.benchmark-search-status) {
   color: var(--muted);
   font-size: 0.8rem;

site/index.html

@@ -768,6 +768,13 @@ <h2 class="benchmark-search-label" id="benchmark-search-heading">
                      class="benchmark-search-input"
                      data-i18n-placeholder="Search benchmarks, tasks, domains…"
                      placeholder="Search benchmarks, tasks, domains…" />
+              <label class="benchmark-model-label" for="benchmark-model-input"
+                     data-i18n="Model with a reported score">Model with a reported score</label>
+              <input id="benchmark-model-input" type="search" autocomplete="off"
+                     class="benchmark-search-input benchmark-model-input"
+                     data-i18n-placeholder="Filter by model, e.g. GPT-6 Sol"
+                     placeholder="Filter by model, e.g. GPT-6 Sol"
+                     aria-controls="benchmark-search-results frontier-benchmark" />
               <p id="benchmark-search-status" class="benchmark-search-status"></p>
               <div id="benchmark-search-results"></div>
               <button id="benchmark-search-more" class="clear-button" type="button" data-i18n="Show more" hidden>Show more</button>

src/benchmark_radar/catalog.py

@@ -675,6 +675,7 @@ def write_catalog(
 def build_benchmark_index(
     records: list[dict[str, Any]],
     series_by_key: dict[str, dict[str, Any]] | None = None,
+    observations: list[dict[str, Any]] | None = None,
 ) -> list[dict[str, Any]]:
     """The small search payload: one entry per source record, never per merge.
 
@@ -684,6 +685,21 @@ def build_benchmark_index(
     it is invisible. One row per record keeps a bad grouping a display bug.
     """
     series_by_key = series_by_key or {}
+    models_by_key: dict[str, dict[str, dict[str, Any]]] = {}
+    for observation in observations or []:
+        name = observation.get("model_name")
+        if not name or not isinstance(observation.get("value"), (int, float)):
+            continue
+        models = models_by_key.setdefault(observation["key"], {})
+        # One model name per source benchmark. Keep the most recent recorded
+        # date and its precision; a model release is not an evaluation update.
+        current = models.get(name)
+        if current is None or (observation.get("reported_date") or "") > (current["date"] or ""):
+            models[name] = {
+                "name": name,
+                "date": observation.get("reported_date"),
+                "date_precision": observation.get("date_precision"),
+            }
     index: list[dict[str, Any]] = []
     for record in records:
         openness = record.get("openness") or {}
@@ -735,6 +751,10 @@ def build_benchmark_index(
                 "openness": openness.get("status", "unknown"),
                 "modality": record.get("modality"),
                 "score_count": series.get("observation_count", 0),
+                "scored_models": sorted(
+                    models_by_key.get(record["key"], {}).values(),
+                    key=lambda model: model["name"].lower(),
+                ),
                 "score_summary": (
                     series.get("score_summary") if series.get("observation_count", 0) else None
                 ),

src/benchmark_radar/cli.py

@@ -449,7 +449,7 @@ def main() -> None:
         # One index over every source, one row per source record. Two sources
         # describing the same benchmark stay two rows until identity.yml says
         # otherwise under human review.
-        index = build_benchmark_index(resolved_records, series_by_key)
+        index = build_benchmark_index(resolved_records, series_by_key, all_observations)
         index_path = write_benchmark_index(
             index,
             Path("site/data/benchmark-index.json"),

tests/score_filters_harness.mjs

@@ -49,10 +49,23 @@ state.benchmarkIndex = [
   {slug:'missing',name:'Missing',source:'llm_stats',score_summary:summary(null,0)},
 ];
 state.lscore = 70;
-const scoreNames = ['scoreRecord','matchesScoreFilter','scoreBrowseRows','saturationRows','scoreRankingRows','benchmarkQueryIds','searchBenchmarkIndex','foldName','frontierDefaultEntry','catalogDisplayFactor'];
+const scoreNames = ['scoreRecord','matchesScoreFilter','scoreBrowseRows','saturationRows','latestMatchingModel','scoreRankingRows','benchmarkQueryIds','searchBenchmarkIndex','foldName','frontierDefaultEntry','catalogDisplayFactor'];
 state.benchmarkQuery = '';
 const scores = new Function('state', 'scorePopulation', 'matchesScoreCutoff', 'SKYLINE_START_DATE', `${scoreNames.map(fn).join('\n')}\nreturn {${scoreNames.join(',')}};`)(state, scorePopulation, matchesScoreCutoff, SKYLINE_START_DATE);
 assert.deepEqual(scores.scoreBrowseRows().map(r=>r.id), ['external','curated','missing']);
+state.benchmarkIndex[0].scored_models = [{name:'GPT-5.6 Sol',date:'2026-06-01',date_precision:'document_publication'}];
+state.benchmarkIndex[1].scored_models = [{name:'GPT-5.6 Sol (high)',date:'2026-09-01',date_precision:'model_announcement'}];
+state.benchmarkModel = 'gpt-5.6-sol';
+assert.deepEqual(scores.saturationRows().map(r=>r.id), ['external','curated'], 'model filtering searches every source beyond the score cutoff and orders by recorded date');
+state.benchmarkModel = 'gpt-6-sol';
+assert.deepEqual(scores.saturationRows(), [], 'an unrecorded model does not imply a benchmark result');
+for (const query of ['-', '---', '()']) {
+  state.benchmarkModel = query;
+  assert.deepEqual(scores.saturationRows(), [], 'punctuation-only queries have no model match');
+}
+assert.equal(state.lscore, 70, 'unmatched model lookup preserves the cutoff');
+state.benchmarkModel = '';
+assert.deepEqual(scores.saturationRows().map(r=>r.id), ['external','curated','missing'], 'clearing the model restores cutoff browsing');
 assert.equal(scores.frontierDefaultEntry(state.data.model_card_leaderboard).id,'external');
 assert.equal(scores.matchesScoreFilter(summary(69.999)),true);
 assert.equal(scores.matchesScoreFilter(summary(70)),false);

tests/test_catalog.py

@@ -71,6 +71,22 @@ def test_search_index_carries_semantic_source_fields_without_inference(normalize
         assert isinstance(row["languages"], list)
 
 
+def test_index_model_filter_evidence_is_scoped_to_its_source_record(normalized: dict) -> None:
+    from benchmark_radar.catalog import build_benchmark_index
+
+    observations = normalized["score_observations"]
+    index = build_benchmark_index(normalized["source_records"], observations=observations)
+    by_key = {record["key"]: record for record in index}
+    for key, record in by_key.items():
+        source_rows = [row for row in observations if row["key"] == key]
+        assert {model["name"] for model in record["scored_models"]} == {
+            row["model_name"] for row in source_rows
+        }
+        assert all(
+            model["date_precision"] == "model_announcement" for model in record["scored_models"]
+        )
+
+
 def test_obs_id_is_unique(normalized: dict) -> None:
     """Without this a rerun silently duplicates every score row."""
     obs_ids = [row["obs_id"] for row in normalized["score_observations"]]
@@ -509,7 +525,14 @@ def test_index_has_one_row_per_source_record(normalized: dict) -> None:
     from benchmark_radar.catalog_opencompass import normalize_opencompass
 
     records = normalized["source_records"] + normalize_opencompass()["source_records"]
-    index = build_benchmark_index(records, {row["key"]: row for row in normalized["score_series"]})
+    series_by_key = {row["key"]: row for row in normalized["score_series"]}
+    unscored_key = next(
+        record["key"] for record in records if record["source"] == "opencompass_hub"
+    )
+    series_by_key[unscored_key] = {"observation_count": 0, "score_summary": {"max": 99}}
+    index = build_benchmark_index(
+        records, series_by_key, observations=normalized["score_observations"]
+    )
     assert len(index) == 1148
     assert len({row["key"] for row in index}) == 1148
     assert len({row["slug"] for row in index}) == 1148
@@ -526,6 +549,8 @@ def test_index_has_one_row_per_source_record(normalized: dict) -> None:
     assert unscored["first_score_source_reference"] is None
     assert unscored["first_score_record"] is None
     assert unscored["score_summary"] is None
+    assert unscored["scored_models"] == []
+    assert any(row["scored_models"] for row in index)
     scored = [row for row in index if row["first_score_record"]]
     assert len(scored) > 600, "the index must preserve dates for the whole scored catalog"
     for row in scored:

tests/test_site.py

@@ -432,7 +432,7 @@ def test_each_view_serializes_only_the_filters_it_reads():
         1
     ].split('if (!utility && state.view === "saturation")', 1)
     assert 'params.set("lfrontier"' not in leaderboard
-    for key in ("lscore", "bq", "lfrontier"):
+    for key in ("lscore", "bq", "bmodel", "lfrontier"):
         assert f'params.set("{key}"' in saturation
     for key in ("lq", "ldomain", "lorg", "lera", "lscore"):
         assert f'params.set("{key}"' in leaderboard
@@ -658,20 +658,23 @@ def section(start: str, end: str) -> str:
   results.legacyBenchmarks.push(window.location.pathname + window.location.search);
 }}
 
-install("/saturation/?lscore=40&bq=bench-95&lfrontier=bench-95&lq=agent&lheight=documents");
+install("/saturation/?lscore=40&bq=bench-95&bmodel=GPT-6+Sol&lfrontier=bench-95&lq=agent&lheight=documents");
 readUrl();
 writeUrl("replace");
 results.saturation = {{
   url: window.location.pathname + window.location.search,
-  view: state.view, query: state.benchmarkQuery, cutoff: state.lscore,
+  view: state.view, query: state.benchmarkQuery, model: state.benchmarkModel, cutoff: state.lscore,
   selected: state.lfrontier, explicit: state.lfrontierExplicit,
 }};
 state.view = "leaderboard";
 writeUrl("push");
 results.sharedCutoff = window.location.pathname + window.location.search;
 state.view = "saturation";
 state.benchmarkQuery = "";
+state.benchmarkModel = "";
 writeUrl("replace");
+readUrl();
+results.clearedModel = state.benchmarkModel;
 results.clearedSearch = window.location.pathname + window.location.search;
 
 install("/#rubric=2");
@@ -733,14 +736,16 @@ def section(start: str, end: str) -> str:
         * 2
     )
     assert routes["saturation"] == {
-        "url": "/saturation/?lscore=40&bq=bench-95&lfrontier=bench-95",
+        "url": "/saturation/?lscore=40&bq=bench-95&bmodel=GPT-6+Sol&lfrontier=bench-95",
         "view": "saturation",
         "query": "bench-95",
+        "model": "GPT-6 Sol",
         "cutoff": 40,
         "selected": "bench-95",
         "explicit": True,
     }
     assert routes["sharedCutoff"] == "/leaderboard/?lscore=40&lheight=documents&lq=agent"
+    assert routes["clearedModel"] == ""
     assert routes["clearedSearch"] == "/saturation/?lscore=40&lfrontier=bench-95"
     assert routes["legacyRubric"] == "/rubric/?version=2"
     assert routes["legacyReturns"] is False
@@ -3271,3 +3276,50 @@ def test_blog_styles_cannot_reach_the_dashboard():
     assert selectors
     assert all(selector.startswith(".blog-page") for selector in selectors)
     assert "blog-page" not in Path("site/index.html").read_text(encoding="utf-8")
+
+
+def test_model_filter_controls_and_status_have_chinese_translations():
+    import json
+    import shutil
+    import subprocess
+
+    import pytest
+
+    node = shutil.which("node")
+    if not node:
+        pytest.skip("node is not installed")
+    script = Path("site/assets/app.js").read_text(encoding="utf-8")
+    html = Path("site/index.html").read_text(encoding="utf-8")
+    keys = [
+        "Model with a reported score",
+        "Filter by model, e.g. GPT-6 Sol",
+        "Model release",
+        "Document published",
+        "Searching all benchmarks (score cutoff paused)",
+    ]
+    assert f'data-i18n="{keys[0]}"' in html
+    assert f'data-i18n-placeholder="{keys[1]}"' in html
+    start = script.index("const I18N = {")
+    dictionary = script[start : script.index("\n};", start) + 3]
+    start = script.index("function t(")
+    translate = script[start : script.index("\n}\n", start) + 2]
+    program = (
+        dictionary
+        + translate
+        + "\nlet lang = 'zh'; function getLang() { return lang; }\n"
+        + f"const keys = {json.dumps(keys)};\n"
+        + "const zh = keys.map(key => t(key)); lang = 'en';\n"
+        + "console.log(JSON.stringify({zh, en: keys.map(key => t(key))}));"
+    )
+    result = subprocess.run(
+        [node, "-e", program], capture_output=True, text=True, timeout=60, check=True
+    )
+    translated = json.loads(result.stdout)
+    assert translated["en"] == keys
+    assert translated["zh"] == [
+        "已有报告成绩的模型",
+        "按模型筛选，例如 GPT-6 Sol",
+        "模型发布日期",
+        "文档发布日期",
+        "搜索全部 benchmark（暂不按分数筛选）",
+    ]