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      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 96.45
    },
    {
      "name": "DeepSeek Coder 33B",
      "modelGroup": "DeepSeek Coder 33B",
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      "confidenceLow": 84.2,
      "confidenceHigh": 103.38,
      "releaseDate": "2023-11-02",
      "organization": "DeepSeek,Peking University",
      "country": "China",
      "accessibility": "Open weights (restricted use)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 96.45
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    {
      "name": "Falcon-7B",
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      "confidenceLow": 82.44,
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      "releaseDate": "2023-04-24",
      "organization": "Technology Innovation Institute",
      "country": "United Arab Emirates",
      "accessibility": "Open weights (unrestricted)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 95.23
    },
    {
      "name": "CodeQwen1.5-7B",
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      "confidenceLow": 80.78,
      "confidenceHigh": 103.36,
      "releaseDate": "2024-04-15",
      "organization": null,
      "country": null,
      "accessibility": "Unknown",
      "accessGroup": "Other",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 94.99
    },
    {
      "name": "vicuna-13b-v1.1",
      "modelGroup": "vicuna-13b-v1.1",
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      "confidenceLow": 80.99,
      "confidenceHigh": 102.84,
      "releaseDate": "2023-04-12",
      "organization": null,
      "country": null,
      "accessibility": "Unknown",
      "accessGroup": "Other",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 94.8
    },
    {
      "name": "MPT-7B",
      "modelGroup": "MPT-7B",
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      "confidenceLow": 81.66,
      "confidenceHigh": 102.66,
      "releaseDate": "2023-05-05",
      "organization": "MosaicML",
      "country": "United States of America",
      "accessibility": "Open weights (unrestricted)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 94.73
    },
    {
      "name": "Gemma 2B",
      "modelGroup": "Gemma 2B",
      "score": 94.34,
      "confidenceLow": 82.8,
      "confidenceHigh": 101.18,
      "releaseDate": "2024-02-21",
      "organization": "Google DeepMind",
      "country": "United States of America",
      "accessibility": "Open weights (restricted use)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 94.34
    },
    {
      "name": "StarCoder 2 7B",
      "modelGroup": "StarCoder 2 7B",
      "score": 93.7,
      "confidenceLow": 79.05,
      "confidenceHigh": 102.01,
      "releaseDate": "2024-02-20",
      "organization": "Hugging Face,ServiceNow,Nvidia,BigCode",
      "country": "United States of America",
      "accessibility": "Open weights (restricted use)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 93.7
    },
    {
      "name": "XGen-7B",
      "modelGroup": "XGen-7B",
      "score": 93.54,
      "confidenceLow": 81.11,
      "confidenceHigh": 101.04,
      "releaseDate": "2023-06-27",
      "organization": "Salesforce",
      "country": "United States of America",
      "accessibility": "Open weights (unrestricted)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 93.54
    },
    {
      "name": "Qwen-1_8B",
      "modelGroup": "Qwen-1_8B",
      "score": 93.07,
      "confidenceLow": 71.44,
      "confidenceHigh": 102,
      "releaseDate": "2023-11-30",
      "organization": null,
      "country": null,
      "accessibility": "Unknown",
      "accessGroup": "Other",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 93.07
    },
    {
      "name": "open_llama_7b",
      "modelGroup": "open_llama_7b",
      "score": 91.8,
      "confidenceLow": 77.35,
      "confidenceHigh": 99.47,
      "releaseDate": "2023-06-07",
      "organization": null,
      "country": null,
      "accessibility": "Unknown",
      "accessGroup": "Other",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 91.8
    },
    {
      "name": "Phi-1.5",
      "modelGroup": "Phi-1.5",
      "score": 91.68,
      "confidenceLow": 71.13,
      "confidenceHigh": 101.34,
      "releaseDate": "2023-09-11",
      "organization": "Microsoft",
      "country": "United States of America",
      "accessibility": "Open weights (unrestricted)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 91.68
    },
    {
      "name": "Baichuan1-7B",
      "modelGroup": "Baichuan1-7B",
      "score": 90.61,
      "confidenceLow": 77.57,
      "confidenceHigh": 99.38,
      "releaseDate": "2023-06-01",
      "organization": "Baichuan",
      "country": "China",
      "accessibility": "Open weights (non-commercial)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 90.61
    },
    {
      "name": "RedPajama-INCITE-7B-Base",
      "modelGroup": "RedPajama-INCITE-7B-Base",
      "score": 90.58,
      "confidenceLow": 76.49,
      "confidenceHigh": 99.17,
      "releaseDate": "2023-05-04",
      "organization": null,
      "country": null,
      "accessibility": "Unknown",
      "accessGroup": "Other",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 90.58
    },
    {
      "name": "Dolly 2.0-12b",
      "modelGroup": "Dolly 2.0-12b",
      "score": 89.83,
      "confidenceLow": 76.06,
      "confidenceHigh": 97.97,
      "releaseDate": "2023-04-11",
      "organization": "Databricks",
      "country": "United States of America",
      "accessibility": "Open weights (unrestricted)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 89.83
    },
    {
      "name": "DeepSeek Coder 6.7B",
      "modelGroup": "DeepSeek Coder 6.7B",
      "score": 89.77,
      "confidenceLow": 75.59,
      "confidenceHigh": 98.06,
      "releaseDate": "2023-11-02",
      "organization": "DeepSeek,Peking University",
      "country": "China",
      "accessibility": "Open weights (restricted use)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 89.77
    },
    {
      "name": "StarCoder 2 3B",
      "modelGroup": "StarCoder 2 3B",
      "score": 88.92,
      "confidenceLow": 73.32,
      "confidenceHigh": 97.85,
      "releaseDate": "2024-02-22",
      "organization": "Hugging Face,ServiceNow,Nvidia,BigCode",
      "country": "United States of America",
      "accessibility": "Open weights (restricted use)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 88.92
    },
    {
      "name": "Qwen2.5-Coder-0.5B",
      "modelGroup": "Qwen2.5-Coder-0.5B",
      "score": 88.31,
      "confidenceLow": 63.95,
      "confidenceHigh": 100.06,
      "releaseDate": "2024-09-18",
      "organization": null,
      "country": null,
      "accessibility": "Unknown",
      "accessGroup": "Other",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 88.31
    },
    {
      "name": "Cerebras-GPT-13B",
      "modelGroup": "Cerebras-GPT-13B",
      "score": 83.42,
      "confidenceLow": 67.04,
      "confidenceHigh": 92.07,
      "releaseDate": "2023-03-20",
      "organization": "Cerebras Systems",
      "country": "United States of America",
      "accessibility": "Open weights (unrestricted)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 83.42
    },
    {
      "name": "DeepSeek Coder 1.3B",
      "modelGroup": "DeepSeek Coder 1.3B",
      "score": 63.88,
      "confidenceLow": 45.1,
      "confidenceHigh": 76.94,
      "releaseDate": "2023-11-02",
      "organization": "DeepSeek,Peking University",
      "country": "China",
      "accessibility": "Open weights (restricted use)",
      "accessGroup": "Open weights",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 63.88
    },
    {
      "name": "stablelm-tuned-alpha-7b",
      "modelGroup": "stablelm-tuned-alpha-7b",
      "score": 56.05,
      "confidenceLow": 31.31,
      "confidenceHigh": 73.19,
      "releaseDate": "2023-04-19",
      "organization": null,
      "country": null,
      "accessibility": "Unknown",
      "accessGroup": "Other",
      "sourceUrl": "https://epoch.ai/eci",
      "eci": 56.05
    }
  ],
  "benchmarks": [
    {
      "name": "GPQA diamond",
      "sourceFile": "gpqa_diamond.csv",
      "scale": 1,
      "randomBaseline": 0.25,
      "scoreCeiling": 1,
      "releaseDate": "2023-11-20",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "FrontierMath-2025-02-28-Private",
      "sourceFile": "frontiermath.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 0.57,
      "releaseDate": "2025-02-28",
      "supersededBy": "FrontierMath-Tiers-1-3-v2-Private",
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "FrontierMath-Tier-4-2025-07-01-Private",
      "sourceFile": "frontiermath_tier_4.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 0.6,
      "releaseDate": "2025-07-11",
      "supersededBy": "FrontierMath-Tier-4-v2-Private",
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "FrontierMath-Tiers-1-3-v2-Private",
      "sourceFile": "frontiermath_tiers_1_3_v2.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 1,
      "releaseDate": "2026-06-12",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "FrontierMath-Tier-4-v2-Private",
      "sourceFile": "frontiermath_tier_4_v2.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 1,
      "releaseDate": "2026-06-12",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "MATH level 5",
      "sourceFile": "math_level_5.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 1,
      "releaseDate": "2021-03-05",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "OTIS Mock AIME 2024-2025",
      "sourceFile": "otis_mock_aime_2024_2025.csv",
      "scale": 1,
      "randomBaseline": 0.001,
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      "releaseDate": "2024-12-19",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "SWE-Bench verified",
      "sourceFile": "swe_bench_verified.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 1,
      "releaseDate": "2024-08-13",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "SimpleQA Verified",
      "sourceFile": "simpleqa_verified.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 1,
      "releaseDate": "2025-09-09",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "Chess Puzzles",
      "sourceFile": "chess_puzzles.csv",
      "scale": 1,
      "randomBaseline": 0.0496,
      "scoreCeiling": 1,
      "releaseDate": "2025-12-10",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "EBR-bench",
      "sourceFile": "ebr_bench.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 1,
      "releaseDate": "2026-07-01",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "Mystery Game Puzzles",
      "sourceFile": "mystery_game_puzzles.csv",
      "scale": 1,
      "randomBaseline": 0.0922,
      "scoreCeiling": 1,
      "releaseDate": "2026-07-30",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "MirrorCode",
      "sourceFile": "mirrorcode.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 1,
      "releaseDate": "2026-06-26",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "Furniture Assembly",
      "sourceFile": "furniture_assembly.csv",
      "scale": 1,
      "randomBaseline": 0.3,
      "scoreCeiling": 1,
      "releaseDate": "2026-09-23",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    },
    {
      "name": "SpireClimb",
      "sourceFile": "spireclimb.csv",
      "scale": 1,
      "randomBaseline": 0,
      "scoreCeiling": 1,
      "releaseDate": "2026-10-14",
      "supersededBy": null,
      "inECI": true,
      "url": "https://epoch.ai/benchmarks/use-this-data",
      "description": "Epoch-administered evaluation. See source method and run settings; scores are not interchangeable across tasks."
    }
  ],
  "papers": [
    {
      "id": "2406.13352v3",
      "title": "AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents",
      "authors": [
        "Edoardo Debenedetti",
        "Jie Zhang",
        "Mislav Balunović",
        "Luca Beurer-Kellner",
        "Marc Fischer",
        "Florian Tramèr"
      ],
      "publishedAt": "2024-06-19T08:55:56Z",
      "updatedAt": "2024-11-24T22:04:23Z",
      "categories": [
        "cs.CR",
        "cs.LG"
      ],
      "url": "https://arxiv.org/abs/2406.13352v3",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Selected methodological reference",
      "published": "2024-06-19T08:55:56Z",
      "summary": "Selected methodological reference"
    },
    {
      "id": "2503.13657v3",
      "title": "Why Do Multi-Agent LLM Systems Fail?",
      "authors": [
        "Mert Cemri",
        "Melissa Z. Pan",
        "Shuyi Yang",
        "Lakshya A. Agrawal",
        "Bhavya Chopra",
        "Rishabh Tiwari",
        "Kurt Keutzer",
        "Aditya Parameswaran",
        "Dan Klein",
        "Kannan Ramchandran",
        "Matei Zaharia",
        "Joseph E. Gonzalez",
        "Ion Stoica"
      ],
      "publishedAt": "2025-03-17T19:04:38Z",
      "updatedAt": "2025-10-26T23:25:18Z",
      "categories": [
        "cs.AI"
      ],
      "url": "https://arxiv.org/abs/2503.13657v3",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Selected methodological reference",
      "published": "2025-03-17T19:04:38Z",
      "summary": "Selected methodological reference"
    },
    {
      "id": "2602.19843v1",
      "title": "MAS-FIRE: Fault Injection and Reliability Evaluation for LLM-Based Multi-Agent Systems",
      "authors": [
        "Jin Jia",
        "Zhiling Deng",
        "Zhuangbin Chen",
        "Yingqi Wang",
        "Zibin Zheng"
      ],
      "publishedAt": "2026-02-23T13:47:43Z",
      "updatedAt": "2026-02-23T13:47:43Z",
      "categories": [
        "cs.SE",
        "cs.AI"
      ],
      "url": "https://arxiv.org/abs/2602.19843v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Selected methodological reference",
      "published": "2026-02-23T13:47:43Z",
      "summary": "Selected methodological reference"
    },
    {
      "id": "2406.12045v1",
      "title": "$τ$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains",
      "authors": [
        "Shunyu Yao",
        "Noah Shinn",
        "Pedram Razavi",
        "Karthik Narasimhan"
      ],
      "publishedAt": "2024-06-17T19:33:08Z",
      "updatedAt": "2024-06-17T19:33:08Z",
      "categories": [
        "cs.AI",
        "cs.CL"
      ],
      "url": "https://arxiv.org/abs/2406.12045v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Selected methodological reference",
      "published": "2024-06-17T19:33:08Z",
      "summary": "Selected methodological reference"
    },
    {
      "id": "2609.04611v1",
      "title": "$τ^τ$-Bench: An Environment for End-To-End, Realistic Agent Construction",
      "authors": [
        "Quan Shi",
        "Keshav Dhandhania",
        "Karthik Narasimhan",
        "Victor Barres"
      ],
      "publishedAt": "2026-09-04T01:23:47Z",
      "updatedAt": "2026-09-04T01:23:47Z",
      "categories": [
        "cs.AI"
      ],
      "url": "https://arxiv.org/abs/2609.04611v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Selected methodological reference",
      "published": "2026-09-04T01:23:47Z",
      "summary": "Selected methodological reference"
    },
    {
      "id": "2610.22341v1",
      "title": "3DCodeVerse: Exploring 3D Worlds as Code",
      "authors": [
        "Yipeng Gao",
        "Ziyao Zeng",
        "Jinfa Huang",
        "Yijiang Li",
        "Haolin Xiong",
        "Wang Qin",
        "Xinlei Yu",
        "Youheng Yao",
        "Jie Zhang",
        "Kun-Yu Lin",
        "Rong Liu",
        "Yinyuan Zhao",
        "Yajie Zhao",
        "Meiqi Guo",
        "Jiebo Luo",
        "Lei Shu",
        "Yunhao Ge",
        "Xinyu Hu",
        "Laurent Itti"
      ],
      "publishedAt": "2026-10-15T17:56:07Z",
      "updatedAt": "2026-10-15T17:56:07Z",
      "categories": [
        "cs.CV",
        "cs.AI"
      ],
      "url": "https://arxiv.org/abs/2610.22341v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T17:56:07Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.22322v1",
      "title": "Learning Self-Orchestration in Decentralized Agent Swarms",
      "authors": [
        "Guowei Xu",
        "Zhenting Qi",
        "Amani Kiruga",
        "Himabindu Lakkaraju",
        "Yilun Du"
      ],
      "publishedAt": "2026-10-15T17:51:57Z",
      "updatedAt": "2026-10-15T17:51:57Z",
      "categories": [
        "cs.MA",
        "cs.AI",
        "cs.CL"
      ],
      "url": "https://arxiv.org/abs/2610.22322v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T17:51:57Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.22319v1",
      "title": "A team of Gemini 4 Argon agents beats Minecraft",
      "authors": [
        "Maxence Faldor",
        "Satinder Singh",
        "Roberta Raileanu"
      ],
      "publishedAt": "2026-10-15T17:51:32Z",
      "updatedAt": "2026-10-15T17:51:32Z",
      "categories": [
        "cs.AI"
      ],
      "url": "https://arxiv.org/abs/2610.22319v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T17:51:32Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.22316v1",
      "title": "Learning to Steer LLM Agents and Multi-Agent Systems",
      "authors": [
        "Leyang Shen",
        "Yaxin Gong",
        "Yang Zhang",
        "Chenxiao Fan",
        "Jiakai Wang",
        "Dong Wang",
        "Yang Liu",
        "Fuli Feng",
        "Chun Kai Ling",
        "Tat-Seng Chua"
      ],
      "publishedAt": "2026-10-15T17:51:17Z",
      "updatedAt": "2026-10-15T17:51:17Z",
      "categories": [
        "cs.LG",
        "cs.AI",
        "cs.MA"
      ],
      "url": "https://arxiv.org/abs/2610.22316v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T17:51:17Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.22292v1",
      "title": "CAT-alyzing Honesty: Continuous Adversarial Training for Transferable LLM Honesty",
      "authors": [
        "Yuan-Chen Chang",
        "Niklas Herbster",
        "Gauthier Gidel",
        "Tommaso Tosato"
      ],
      "publishedAt": "2026-10-15T17:43:47Z",
      "updatedAt": "2026-10-15T17:43:47Z",
      "categories": [
        "cs.LG",
        "cs.CL",
        "cs.CY"
      ],
      "url": "https://arxiv.org/abs/2610.22292v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T17:43:47Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.22195v1",
      "title": "HTN-Orchestrate: A Hierarchical Task Network Framework for Multi-Agent Orchestration",
      "authors": [
        "Yanchen Deng",
        "Jianguo Huang",
        "Yao Long Teng",
        "Yixuan Li",
        "Handuo Zhang",
        "Ning Wang",
        "Liangcai Su",
        "Xinyu Wang",
        "Bo An"
      ],
      "publishedAt": "2026-10-15T16:45:59Z",
      "updatedAt": "2026-10-15T16:45:59Z",
      "categories": [
        "cs.AI",
        "cs.CL"
      ],
      "url": "https://arxiv.org/abs/2610.22195v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T16:45:59Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.22194v1",
      "title": "AutoSFT: An Agentic System for Automated Data Research in Supervised Fine-Tuning",
      "authors": [
        "Bingxiang He",
        "Pengqi Sun",
        "Shihao Peng",
        "Shaoxuan Li",
        "Huiyu Xiao",
        "Hongjian Shi",
        "Zixuan Fu",
        "Ziqing Qiao",
        "Yuxin Zuo",
        "Cheng Qian",
        "Xinqiang Yu",
        "Jiayi Li",
        "Xiusi Chen",
        "Yizhen Song",
        "Xiangyang Wang",
        "Iofai Lei",
        "Yudong Wang",
        "Ning Ding",
        "Zhiyuan Liu",
        "Xiaozhi Wang",
        "Chaojun Xiao"
      ],
      "publishedAt": "2026-10-15T16:44:34Z",
      "updatedAt": "2026-10-15T16:44:34Z",
      "categories": [
        "cs.AI",
        "cs.CL"
      ],
      "url": "https://arxiv.org/abs/2610.22194v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T16:44:34Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.22138v1",
      "title": "Believed but Not Said: Measuring Hidden Belief Collapse in Multi-Agent LLM Discussions",
      "authors": [
        "Liangjie Huang",
        "Henry Peng Zou",
        "Wei-Chieh Huang",
        "Wooseong Yang",
        "Yuwei Han",
        "Philip S. Yu"
      ],
      "publishedAt": "2026-10-15T16:12:07Z",
      "updatedAt": "2026-10-15T16:12:07Z",
      "categories": [
        "cs.AI",
        "cs.CL",
        "cs.MA"
      ],
      "url": "https://arxiv.org/abs/2610.22138v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T16:12:07Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.22124v1",
      "title": "PROBE: Learning to Audit Policy Compliance in Tool-Using LLM Agents",
      "authors": [
        "Kshitij Mishra",
        "Abhijith Sharma",
        "Nils Lukas",
        "Salem Lahlou"
      ],
      "publishedAt": "2026-10-15T16:01:38Z",
      "updatedAt": "2026-10-15T16:01:38Z",
      "categories": [
        "cs.AI"
      ],
      "url": "https://arxiv.org/abs/2610.22124v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T16:01:38Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.22039v1",
      "title": "WEAVE: Weaving Real-World Code Evolution into Dependency-Structured Tasks for Benchmarking and Training Code Agents",
      "authors": [
        "Weihao Li",
        "Zihang Xu",
        "Zhongqiu Wang",
        "Songwei Yu",
        "Wenqiang Zhu",
        "Yuechen Luo",
        "Jingxuan Xu",
        "Yanan Wu",
        "Haoyang Huang",
        "Ken Deng"
      ],
      "publishedAt": "2026-10-15T15:12:56Z",
      "updatedAt": "2026-10-15T15:12:56Z",
      "categories": [
        "cs.SE",
        "cs.CL"
      ],
      "url": "https://arxiv.org/abs/2610.22039v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T15:12:56Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.21914v1",
      "title": "CodeHealth Predicts the Token Cost of Agentic Code Review: A Pre-Registered Study of 465 Agent-Authored Pull Requests",
      "authors": [
        "Lo Gullstrand Heander",
        "Markus Borg",
        "Emma Söderberg",
        "Christofer Rydenfält"
      ],
      "publishedAt": "2026-10-15T14:00:33Z",
      "updatedAt": "2026-10-15T14:00:33Z",
      "categories": [
        "cs.SE",
        "cs.AI"
      ],
      "url": "https://arxiv.org/abs/2610.21914v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T14:00:33Z",
      "summary": "Automated discovery; editorial review pending"
    },
    {
      "id": "2610.21912v1",
      "title": "Learning Rewards in Strategic Games",
      "authors": [
        "Antoine Bergerault",
        "Cyrille Kone",
        "Giorgia Ramponi"
      ],
      "publishedAt": "2026-10-15T13:59:45Z",
      "updatedAt": "2026-10-15T13:59:45Z",
      "categories": [
        "cs.GT",
        "cs.AI",
        "cs.LG",
        "cs.MA"
      ],
      "url": "https://arxiv.org/abs/2610.21912v1",
      "reviewStatus": "Preprint metadata; publication status has not been independently reviewed",
      "selection": "Automated discovery; editorial review pending",
      "published": "2026-10-15T13:59:45Z",
      "summary": "Automated discovery; editorial review pending"
    }
  ],
  "sources": [
    {
      "name": "Epoch AI",
      "url": "https://epoch.ai/data/benchmark_data.zip",
      "documentation": "https://epoch.ai/benchmarks/use-this-data",
      "license": "CC BY 4.0",
      "licenseUrl": "https://creativecommons.org/licenses/by/4.0/",
      "attribution": "Epoch AI, Capabilities & benchmarking. Retrieved from epoch.ai. MEKreflect has selected fields and reformatted the data; no affiliation or endorsement is implied.",
      "retrievedAt": "2026-10-16T15:15:40.854Z",
      "sourceLastModified": null,
      "archiveSHA256": "63a2858b29f782d8a2d39a0d3feb7752da6e38ab764a24d7e626919a689c61d1",
      "coverage": {
        "eciModelGroups": 277,
        "sourceModelVersions": 1149,
        "importedInternalBenchmarks": 15,
        "importedRunRows": 1600,
        "includesAllModels": false,
        "selection": "Every valid model group in the downloaded Epoch Capabilities Index; internal benchmark tables listed in the archive metadata. Externally administered benchmark tables are excluded from this local import."
      },
      "interpretation": "ECI is Epoch’s fitted capability scale, not a percentage or an operational success rate. Scores depend on source coverage and evaluation settings. Confidence bounds are supplied by Epoch. Empty fields remain null. MEKreflect has not rerun these evaluations."
    },
    {
      "name": "arXiv",
      "url": "https://export.arxiv.org/api/query?search_query=(cat%3Acs.AI%20OR%20cat%3Acs.CL)%20AND%20(all%3A%22multi-agent%22%20OR%20all%3A%22agent%20evaluation%22)&sortBy=submittedDate&sortOrder=descending&start=0&max_results=12",
      "documentation": "https://info.arxiv.org/help/api/tou.html",
      "license": "CC0 1.0 descriptive metadata",
      "licenseUrl": "https://creativecommons.org/publicdomain/zero/1.0/",
      "attribution": "arXiv metadata supplied by the authors and arXiv. Papers remain their authors’ work. Inclusion is discovery, not peer review or endorsement.",
      "retrievedAt": "2026-10-16T15:15:44.057Z",
      "selectedQuery": "https://export.arxiv.org/api/query?id_list=2503.13657,2406.12045,2602.19843,2406.13352,2609.04611&max_results=5",
      "query": "(cat:cs.AI OR cat:cs.CL) AND (all:\"multi-agent\" OR all:\"agent evaluation\")",
      "selection": "Five selected references plus the twelve most recently submitted records matching a bounded agent-evaluation query. This is a discovery feed, not a complete literature review."
    }
  ],
  "regional": [
    {
      "id": "eu-ai-adoption",
      "title": "One in five EU enterprises reported using AI in 2025",
      "publisher": "Eurostat",
      "publishedAt": "2025-12-11",
      "checkedAt": "2026-10-16",
      "url": "https://ec.europa.eu/eurostat/web/products-eurostat-news/w/ddn-20251211-2",
      "topic": "Adoption and use",
      "countries": [
        "European Union"
      ],
      "metric": {
        "value": 20,
        "unit": "% of surveyed enterprises",
        "year": 2025,
        "previousValue": 13.5,
        "previousYear": 2024
      },
      "summary": "The official enterprise survey records wider adoption. It does not tell us whether an AI workflow is reliable or how much useful work it completes.",
      "scope": "EU enterprises with ten or more employees in the survey scope. This figure is not a Western Balkans adoption estimate.",
      "researchQuestion": "What changes after adoption: accepted output, review effort, error rates and staff capability?"
    },
    {
      "id": "balkans-antennas",
      "title": "North Macedonia and Serbia connect to the AI Factory network",
      "publisher": "European Commission",
      "publishedAt": "2025-10-13",
      "checkedAt": "2026-10-16",
      "url": "https://digital-strategy.ec.europa.eu/en/news/eu-announces-ai-factories-antennas-across-member-states-and-partner-countries",
      "topic": "Balkans and infrastructure",
      "countries": [
        "North Macedonia",
        "Serbia"
      ],
      "summary": "The Commission announced AI Factory Antennas in both countries. This creates a concrete regional research agenda around access, skills and the ability of local organisations to use shared infrastructure.",
      "scope": "An infrastructure announcement does not establish that a particular company has received access or achieved operational gains.",
      "researchQuestion": "Which local organisations can turn access to compute into a useful, evaluated workflow?"
    },
    {
      "id": "antenna-directory",
      "title": "VEZILKA and SAIFA are listed in Europe’s AI Factory ecosystem",
      "publisher": "European Commission",
      "publishedAt": null,
      "checkedAt": "2026-10-16",
      "url": "https://digital-strategy.ec.europa.eu/en/policies/ai-factories",
      "topic": "Balkans and infrastructure",
      "countries": [
        "North Macedonia",
        "Serbia"
      ],
      "summary": "The official directory names VEZILKA in North Macedonia and SAIFA in Serbia. The directory provides a starting point for tracking regional institutions and access routes.",
      "scope": "Directory inclusion is not a measure of compute use, project success or economic impact.",
      "researchQuestion": "How do access requirements, training provision and institutional capacity affect smaller organisations?"
    },
    {
      "id": "digital-europe-access",
      "title": "Digital Europe creates a regional route to participation",
      "publisher": "European Commission",
      "publishedAt": "2023-06-30",
      "checkedAt": "2026-10-16",
      "url": "https://digital-strategy.ec.europa.eu/en/news/digital-europe-programme-opens-candidate-countries-montenegro-north-macedonia-albania-and-serbia",
      "topic": "Balkans and institutions",
      "countries": [
        "Montenegro",
        "North Macedonia",
        "Albania",
        "Serbia"
      ],
      "summary": "Association agreements connected four Western Balkan countries to Digital Europe funding opportunities. Eligibility must still be checked against each current call.",
      "scope": "This is a historical policy milestone, not an open funding call or a claim that MEKreflect has funding.",
      "researchQuestion": "What prevents operational teams from converting available programmes into well-scoped, sustainable projects?"
    },
    {
      "id": "eu-strategic-adoption",
      "title": "AI uptake is spreading across Europe’s strategic sectors",
      "publisher": "European Commission Joint Research Centre",
      "publishedAt": "2026-10-14",
      "checkedAt": "2026-10-16",
      "url": "https://joint-research-centre.ec.europa.eu/jrc-news-and-updates/ai-adoption-more-doubles-almost-every-eu-strategic-sector-2026-10-14_en",
      "topic": "Industry and adoption",
      "countries": [
        "European Union"
      ],
      "summary": "A new JRC analysis follows adoption across sectors using Eurostat enterprise data. Sector differences make a single generic adoption story inadequate.",
      "scope": "Survey adoption and demonstrated effectiveness answer different questions. The source does not provide a MEKreflect effectiveness estimate.",
      "researchQuestion": "Which sector-specific controls and skills are needed after a team introduces AI?"
    }
  ]
}