🗺️ Excited to share our comprehensive survey on agentic artifact creation!<br>We reviewed 200+ papers across six families (textual, vision, audio, video, spatio, and behavioral).</p>\n<p>We frame them as a stateful construction process with three key components (Operational Representation, Construction Policy, Runtime Verification). We hope this survey serves as a valuable reference for advancing foundations and applications of agentic AI.</p>\n","updatedAt":"2026-08-31T07:54:28.769Z","author":{"_id":"63bb1845df5897db7f0431ea","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/63bb1845df5897db7f0431ea/1v1JP13Gsp7nYpwruijBh.jpeg","fullname":"Gemini Wang","name":"GeminiLight","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":1,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.8961732983589172},"editors":["GeminiLight"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/63bb1845df5897db7f0431ea/1v1JP13Gsp7nYpwruijBh.jpeg"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2608.28122","authors":[{"_id":"6a9532c6073195fee515733c","name":"Tianfu Wang","hidden":false},{"_id":"6a9532c6073195fee515733d","name":"Zhezheng Hao","hidden":false},{"_id":"6a9532c6073195fee515733e","name":"Xilin Xia","hidden":false},{"_id":"6a9532c6073195fee515733f","name":"Lixin Liu","hidden":false},{"_id":"6a9532c6073195fee5157340","name":"Mengkang Hu","hidden":false},{"_id":"6a9532c6073195fee5157341","name":"Hongzhang Liu","hidden":false},{"_id":"6a9532c6073195fee5157342","name":"Xi Chen","hidden":false},{"_id":"6a9532c6073195fee5157343","name":"Ziyan Liu","hidden":false},{"_id":"6a9532c6073195fee5157344","name":"Xiankun Lin","hidden":false},{"_id":"6a9532c6073195fee5157345","name":"Weijia Zhang","hidden":false},{"_id":"6a9532c6073195fee5157346","name":"Nicholas Jing Yuan","hidden":false},{"_id":"6a9532c6073195fee5157347","name":"Hui Xiong","hidden":false}],"publishedAt":"2026-08-28T00:00:00.000Z","submittedOnDailyAt":"2026-08-31T00:00:00.000Z","title":"Agentic Artifact Creation: Systems, Evaluation, Principles, and Opportunities","submittedOnDailyBy":{"_id":"63bb1845df5897db7f0431ea","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/63bb1845df5897db7f0431ea/1v1JP13Gsp7nYpwruijBh.jpeg","isPro":false,"fullname":"Gemini Wang","user":"GeminiLight","type":"user","name":"GeminiLight"},"summary":"Generative models can turn natural-language prompts into images, text, code, and other content, lowering the cost of producing drafts and components. Their practical impact increasingly depends on whether those pieces can become complete, dependable deliverables. This survey examines agentic artifact creation, which we define as stateful construction in which an AI system materially constructs or revises a deliverable and intermediate observations redirect later work. Functionally, the process links an operational representation of the artifact, a construction policy, and runtime verification whose feedback can redirect later actions. We reviewed 259 works available through August 20, 2026: 230 systems meeting this definition and 29 benchmarks of agentic artifact construction. We compare six artifact families, then analyze application settings and evaluation practice as separate dimensions. Across families, construction challenges reflect not only modality but also how tightly decisions are coupled and whether failures become visible while they remain repairable. Decomposition can reduce local complexity while increasing coordination and reassembly costs. Learned judges may add little independent evidence when they share the generator's preferences or blind spots. We formulate principles for keeping commitments and responsibility explicit, turning feedback into targeted repair, and revalidating affected state after change. We also identify opportunities for sustaining coherent, accountable control as artifacts, creator intent, and construction systems evolve. A curated paper list is available at https://github.com/GeminiLight/awesome-agentic-artifact-creation.","upvotes":48,"discussionId":"6a9532c6073195fee5157348","projectPage":"https://agentic-creation.github.io/","githubRepo":"https://github.com/GeminiLight/awesome-agentic-artifact-creation","githubRepoAddedBy":"user","ai_summary":"This survey defines agentic artifact creation as stateful, feedback-driven construction of deliverables by AI systems and analyzes 259 works across artifact families, settings, and evaluation practices to propose principles for accountable control.","ai_keywords":["generative models"],"ai_summary_model":"thinkingmachines/Inkling-Small","githubStars":14,"organization":{"_id":"665abecde9121df9e6e43e33","name":"HKUST-GZ2","fullname":"Hong Kong University of Science and Technology(GuangZhou)","avatar":"https://www.gravatar.com/avatar/df3d0f963dc7e28f1d51efe4f494cd32?d=retro&size=100"}},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[{"_id":"63bb1845df5897db7f0431ea","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/63bb1845df5897db7f0431ea/1v1JP13Gsp7nYpwruijBh.jpeg","isPro":false,"fullname":"Gemini Wang","user":"GeminiLight","type":"user"},{"_id":"67e75c08f5380cbbeadd9ec6","avatarUrl":"/avatars/2facc6ecb6ccb5fff56960d495375726.svg","isPro":false,"fullname":"AAA","user":"AAA-cc","type":"user"},{"_id":"6710f28663510b26bc59b023","avatarUrl":"/avatars/545559ed841cc84a2ff3c84727e39928.svg","isPro":false,"fullname":"Yang Hongli","user":"HugLily","type":"user"},{"_id":"68bec04b97d54fa252297005","avatarUrl":"/avatars/4109d4d60aee0b5845f211dfda3860d0.svg","isPro":false,"fullname":"kayl hao","user":"zzzzzzzzzzhao","type":"user"},{"_id":"6a36b1446df8a6a8037113d3","avatarUrl":"/avatars/812cfff8ece54c9b451a93e88b80d854.svg","isPro":false,"fullname":"ruohan shi","user":"srhsm","type":"user"},{"_id":"6777aeedcd9c943549b26527","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/wTusgCoTbVqvu2jeaebcP.png","isPro":false,"fullname":"liu","user":"ziyan2003","type":"user"},{"_id":"6517eb8ece732bf33a2e5001","avatarUrl":"/avatars/c83d6e3dc178c41d3168d2c2d9094c9e.svg","isPro":false,"fullname":"wwwchang","user":"chang04","type":"user"},{"_id":"6a2c2d978e231302901a97ad","avatarUrl":"/avatars/b72097e3e71a0d235ed740b9af2a7850.svg","isPro":false,"fullname":"lxy","user":"linxinyi2002","type":"user"},{"_id":"6a95362774541f101ec47873","avatarUrl":"/avatars/9313c5976d7bac3e7882ace575515527.svg","isPro":false,"fullname":"liulx","user":"liulx","type":"user"},{"_id":"6a26bc2ce821b0e2673074ce","avatarUrl":"/avatars/05fc6efd1b87dc647e043e8854d3cc56.svg","isPro":false,"fullname":"Yixuan Li","user":"Yixuan87","type":"user"},{"_id":"6433a80ca4c9c55871a38624","avatarUrl":"/avatars/c066881fd22306dd418d5bb7b4e1c096.svg","isPro":false,"fullname":"phy","user":"sanbu","type":"user"},{"_id":"6a95379beb8e26d0c7336c5c","avatarUrl":"/avatars/1f2dffd4d12b5d980989a9413eab9e5b.svg","isPro":false,"fullname":"wojiaogzx","user":"HELL12138","type":"user"}],"acceptLanguages":["en"],"dailyPaperRank":3,"organization":{"_id":"665abecde9121df9e6e43e33","name":"HKUST-GZ2","fullname":"Hong Kong University of Science and Technology(GuangZhou)","avatar":"https://www.gravatar.com/avatar/df3d0f963dc7e28f1d51efe4f494cd32?d=retro&size=100"},"markdownContentUrl":"https://huggingface.co/buckets/huggingchat/papers-content/resolve/2608/2608.28122.md","query":{}}">

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