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flat/objects/0a/00/0a009345-a98e-4b97-9ea9-3886b18d5e39.json

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flat/objects/0a/01/0a01649f-4c07-4e5a-817d-384a5096c2c8.json

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flat/objects/0a/02/0a027d6c-1f70-4519-9bba-b309099aef16.json

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+}

flat/objects/0a/07/0a077fe6-c88d-4331-8d50-3e5153da4d0a.json

@@ -0,0 +1,208 @@
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+}

flat/objects/0a/07/0a07e2e5-dbef-4995-a75b-4c5ff8a11ed2.json

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flat/objects/0a/09/0a09334a-1dfe-44f7-b114-b7942a38720c.json

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flat/objects/0a/0b/0a0b85d6-480b-44f6-9087-5cd00edd0761.json

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flat/objects/0a/0b/0a0ba1ba-49a3-4ac6-ae77-0eb0ca1476c6.json

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flat/objects/0a/0b/0a0bee24-96f3-44ca-843f-c358a8435a9a.json

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+}

flat/objects/0a/0c/0a0ce857-661d-4e26-ad44-0f3c831b63f5.json

@@ -0,0 +1,148 @@
+{
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+}

flat/objects/0a/0e/0a0e87b4-5d20-45b6-8b07-744f1e780b09.json

@@ -0,0 +1,178 @@
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+        "metric_name": "Cache Summary Exact Match on the T1 Small Dataset",
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+}

flat/objects/0a/0f/0a0f5a57-f61d-4692-98d4-8573ada2554d.json

@@ -0,0 +1,115 @@
+{
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+    "inference_platform": "anthropic"
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+        "url": [
+          "https://drchangliu.github.io/WordleArena/results.json"
+        ]
+      },
+      "evaluation_timestamp": "2026-02-17",
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flat/objects/0a/13/0a130be7-d06f-41e1-b92a-de0c6802d1f3.json

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flat/objects/0a/15/0a15c62b-2439-4168-9019-4842939b9918.json

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flat/objects/0a/1a/0a1a66d3-897b-42d7-912b-6e9d8fc3ee3b.json

@@ -0,0 +1,148 @@
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flat/objects/0a/1b/0a1b0abf-b89a-4e28-b71e-a2315fbaff42.json

@@ -0,0 +1,208 @@
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flat/objects/0a/1c/0a1c7a0f-c4f2-4bb7-92a8-6fed4505ec42.json

@@ -0,0 +1,268 @@
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flat/objects/0a/1d/0a1d0b27-ad42-4751-a1d0-3605b32fa3e7.json

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flat/objects/0a/1e/0a1e8504-cb67-42fc-9219-4308cc177d93.json

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flat/objects/0a/20/0a20ed50-4c55-4bab-9e0d-0306e81aa215.json

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+    },
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+        "metric_name": "When2Call Tool Hallucination Rate",
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+}

flat/objects/0a/24/0a241278-c859-4645-a091-4e69c272c80e.json

@@ -0,0 +1,118 @@
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flat/objects/0a/24/0a246060-3a5d-4017-9bed-38cb83384cca.json

@@ -0,0 +1,328 @@
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+    },
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+          "raw_evaluation_name": "WebUI-to-Code: Coarse-Grained Visual Similarity"
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+        "metric_id": "webui_to_code_coarse_grained_visual_similarity",
+        "metric_name": "WebUI-to-Code: Coarse-Grained Visual Similarity",
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+          "alphaxiv_is_primary": "False",
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+        "metric_id": "webui_to_code_code_compilation_success_rate",
+        "metric_name": "WebUI-to-Code: Code Compilation Success Rate",
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+      "evaluation_name": "WebUIBench",
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+        "url": [
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+        ]
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+        "score_type": "continuous",
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+    },
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+        "source_type": "url",
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+    },
+    {
+      "evaluation_name": "WebUIBench",
+      "source_data": {
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+        "source_type": "url",
+        "url": [
+          "https://www.alphaxiv.org/abs/2506.07818"
+        ]
+      },
+      "metric_config": {
+        "lower_is_better": false,
+        "score_type": "continuous",
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+          "alphaxiv_is_primary": "False",
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+        },
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+        "metric_name": "WebUI-to-Code: Text Content Similarity",
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+      },
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+        "source_type": "url",
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+        "metric_name": "Average Performance on WebUI-HTML Understanding Tasks",
+        "metric_kind": "score",
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+      "evaluation_result_id": "WebUIBench/Claude-3.5-Sonnet/1771591481.616601#webuibench#average_performance_on_webui_html_understanding_tasks"
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+        "additional_details": {
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+    },
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+          "alphaxiv_is_primary": "False",
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+        },
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+    }
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+  "eval_library": {
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+}

flat/objects/0a/26/0a26155c-fc45-4a1a-9104-596ed3a3810d.json

@@ -0,0 +1,208 @@
+{
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+  "evaluation_id": "ECHO/Bagel/1771591481.616601",
+  "retrieved_timestamp": "1771591481.616601",
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+    "source_type": "documentation",
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+    "name": "Bagel",
+    "developer": "unknown"
+  },
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+        ]
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+        "metric_name": "Overall Evaluation on ECHO (Image-to-Image)",
+        "metric_kind": "score",
+        "metric_unit": "points"
+      },
+      "score_details": {
+        "score": 0.48
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+      "evaluation_result_id": "ECHO/Bagel/1771591481.616601#echo#overall_evaluation_on_echo_image_to_image"
+    },
+    {
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flat/objects/0a/26/0a268c66-4294-46ee-a92c-84aa313dcf02.json

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flat/objects/0a/2e/0a2e6d7d-ac09-4e94-92c8-0ff6dc91129e.json

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flat/objects/0a/30/0a30fd70-2381-4a4b-89aa-dbd169c856f0.json

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flat/objects/0a/34/0a346418-77fa-4c03-afc5-5289170f4588.json

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flat/objects/0a/35/0a35b6f6-31bb-4c7b-8421-90f1215c4e50.json

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flat/objects/0a/39/0a3944a4-5823-43a8-b2d3-882ffa88af72.json

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flat/objects/0a/39/0a3982d0-dd8e-4b3e-8a16-abc29f7263c9.json

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flat/objects/0a/3a/0a3a7a46-4d58-4d9d-93ad-498166ad742f.json

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flat/objects/0a/3b/0a3b94fc-7dec-44cb-8a5e-657b155376c3.json

@@ -0,0 +1,268 @@
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+        "evaluation_description": "Model performance on the subset of SciVideoBench questions related to the discipline of Biology. This metric measures the ability to reason about experimental videos in areas like biochemistry, neuroscience, and molecular biology.",
+        "additional_details": {
+          "alphaxiv_y_axis": "Accuracy (%) - Biology",
+          "alphaxiv_is_primary": "False",
+          "raw_evaluation_name": "SciVideoBench: Accuracy on Biology Videos"
+        },
+        "metric_id": "scivideobench_accuracy_on_biology_videos",
+        "metric_name": "SciVideoBench: Accuracy on Biology Videos",
+        "metric_kind": "score",
+        "metric_unit": "points"
+      },
+      "score_details": {
+        "score": 28.1
+      },
+      "evaluation_result_id": "SciVideoBench/Qwen3-VL-8B-Instruct/1771591481.616601#scivideobench#scivideobench_accuracy_on_biology_videos"
+    },
+    {
+      "evaluation_name": "SciVideoBench",
+      "source_data": {
+        "dataset_name": "SciVideoBench",
+        "source_type": "url",
+        "url": [
+          "https://huggingface.co/datasets/groundmore/scivideobench"
+        ]
+      },
+      "metric_config": {
+        "lower_is_better": false,
+        "score_type": "continuous",
+        "min_score": 0.0,
+        "max_score": 100.0,
+        "evaluation_description": "Model performance on quantitative reasoning questions in SciVideoBench. This is consistently the most challenging task, requiring models to accurately extract numerical values from visual content, perform multi-step calculations, and apply domain-specific quantitative logic.",
+        "additional_details": {
+          "alphaxiv_y_axis": "Accuracy (%) - Quantitative Reasoning",
+          "alphaxiv_is_primary": "False",
+          "raw_evaluation_name": "SciVideoBench: Quantitative Reasoning Accuracy"
+        },
+        "metric_id": "scivideobench_quantitative_reasoning_accuracy",
+        "metric_name": "SciVideoBench: Quantitative Reasoning Accuracy",
+        "metric_kind": "score",
+        "metric_unit": "points"
+      },
+      "score_details": {
+        "score": 12.7
+      },
+      "evaluation_result_id": "SciVideoBench/Qwen3-VL-8B-Instruct/1771591481.616601#scivideobench#scivideobench_quantitative_reasoning_accuracy"
+    }
+  ],
+  "eval_library": {
+    "name": "alphaxiv",
+    "version": "unknown"
+  }
+}