📊 <strong>ALD/E-ImageMiner</strong> is an expert-annotated multimodal benchmark for understanding scientific figures from atomic layer deposition and atomic layer etching (ALD/E), covering both experimental and simulation studies. It contains 1,951 figures from 205 research papers.</p>\n<p>Evaluate your models and submit results to the four CodaBench leaderboards:</p>\n<ul>\n<li><a href=\"https://www.codabench.org/competitions/12901/\" rel=\"nofollow\">Figure classification</a></li>\n<li><a href=\"https://www.codabench.org/competitions/12902/\" rel=\"nofollow\">Data-table extraction</a></li>\n<li><a href=\"https://www.codabench.org/competitions/12909/\" rel=\"nofollow\">Figure summarization</a></li>\n<li><a href=\"https://www.codabench.org/competitions/12908/\" rel=\"nofollow\">Visual question answering</a></li>\n</ul>\n<p>🤗 <a href=\"https://huggingface.co/datasets/SciKnowOrg/ALD-E-ImageMiner\">Access the complete ALD/E-ImageMiner benchmark dataset on Hugging Face</a></p>\n","updatedAt":"2026-08-04T12:48:40.911Z","author":{"_id":"62a6ea5b321404a711cb17b5","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/gz0LpMPYgrQGm12sQkaQY.png","fullname":"Jennifer D'Souza","name":"jdsouza","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":2,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.7634025812149048},"editors":["jdsouza"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/gz0LpMPYgrQGm12sQkaQY.png"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2607.26848","authors":[{"_id":"6a71c0ba5067ac40957f7c73","name":"Fahad Ahmed","hidden":false},{"_id":"6a71c0ba5067ac40957f7c74","name":"Sören Auer","hidden":false},{"_id":"6a71c0ba5067ac40957f7c75","name":"Jennifer D'Souza","hidden":false}],"mediaUrls":["https://cdn-uploads.huggingface.co/production/uploads/62a6ea5b321404a711cb17b5/qROY9U0kRuruMu9ezhh7w.png"],"publishedAt":"2026-07-29T00:00:00.000Z","submittedOnDailyAt":"2026-08-04T00:00:00.000Z","title":"ICDAR 2026 Competition on Information Extraction from Atomic Layer Deposition/Etching (ALD/E) Scientific Figures","submittedOnDailyBy":{"_id":"62a6ea5b321404a711cb17b5","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/gz0LpMPYgrQGm12sQkaQY.png","isPro":false,"fullname":"Jennifer D'Souza","user":"jdsouza","type":"user","name":"jdsouza"},"summary":"Scientific figure comprehension and reasoning using multimodal AI requires integrating visual perception with domain-specific reasoning to extract meaningful knowledge, often not presented in the text of a research publication. The Sci-ImageMiner benchmark dataset, accompanied by a community-driven competition, raises the bar over prior scientific competitions by curating a comprehensive, expert-annotated dataset across four end-to-end complementary tasks. The competition attracted 68 active participants and 1,263 public/private submissions from 9th January 2026 to 8th April 2026. Our results show that state-of-the-art multimodal models perform well on classification and summarization tasks but struggle with data extraction and scientific reasoning, particularly in visual question-answering. These findings reveal key limitations and highlight challenges and opportunities for improving domain-aware multimodal AI systems. Overall, the Sci-ImageMiner benchmark and competition establish a rigorous platform for advancing research in scientific figure comprehension and reasoning and demonstrate the potential of state-of-the-art approaches for a challenging and complex research area.","upvotes":4,"discussionId":"6a71c0ba5067ac40957f7c76","projectPage":"https://huggingface.co/datasets/SciKnowOrg/ALD-E-ImageMiner","githubRepo":"https://github.com/sciknoworg/ALD-E-ImageMiner","githubRepoAddedBy":"user","githubStars":4,"organization":{"_id":"6747514b0a9564189ae81ae0","name":"SciKnowOrg","fullname":"Scientific Knowledge Organization","avatar":"https://cdn-avatars.huggingface.co/v1/production/uploads/62a6ea5b321404a711cb17b5/wUv2FmvDm25Xvf1yuwoSG.jpeg"}},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[{"_id":"62a6ea5b321404a711cb17b5","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/gz0LpMPYgrQGm12sQkaQY.png","isPro":false,"fullname":"Jennifer D'Souza","user":"jdsouza","type":"user"},{"_id":"69bb9cf014e86456053e01a4","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/hLYpKNdgUU2jM1MxM5deo.png","isPro":false,"fullname":"김수아","user":"gracehall","type":"user"},{"_id":"69bce28a374a079a5d1989b1","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/xPWYuTece0_D9RTpZuYqi.png","isPro":false,"fullname":"Grace Johnson","user":"lyichenvo","type":"user"},{"_id":"639a16f657595ea3838ad1fb","avatarUrl":"/avatars/81e07080b45e4157278b8eda8225ec3e.svg","isPro":false,"fullname":"Fahad Ahmed","user":"sfahadahmed","type":"user"}],"acceptLanguages":["en"],"dailyPaperRank":0,"organization":{"_id":"6747514b0a9564189ae81ae0","name":"SciKnowOrg","fullname":"Scientific Knowledge Organization","avatar":"https://cdn-avatars.huggingface.co/v1/production/uploads/62a6ea5b321404a711cb17b5/wUv2FmvDm25Xvf1yuwoSG.jpeg"},"markdownContentUrl":"https://huggingface.co/buckets/huggingchat/papers-content/resolve/2607/2607.26848.md","query":{}}">

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