<a href=\"https://cdn-uploads.huggingface.co/production/uploads/6576ace7769f3ee9bd7b1b88/emoKJb3GHvVGTGZ1IuGni.png\" rel=\"nofollow\"><img src=\"https://cdn-uploads.huggingface.co/production/uploads/6576ace7769f3ee9bd7b1b88/emoKJb3GHvVGTGZ1IuGni.png\" alt=\"concept\"></a></p>\n","updatedAt":"2026-05-22T13:07:05.440Z","author":{"_id":"6576ace7769f3ee9bd7b1b88","avatarUrl":"/avatars/5b5921e54413a37afde6ce017809c86e.svg","fullname":"Eunsu Kim","name":"EunsuKim","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":4,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.3792494535446167},"editors":["EunsuKim"],"editorAvatarUrls":["/avatars/5b5921e54413a37afde6ce017809c86e.svg"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2605.21363","authors":[{"_id":"6a1054c6a53a61ce2e422fcf","user":{"_id":"6576ace7769f3ee9bd7b1b88","avatarUrl":"/avatars/5b5921e54413a37afde6ce017809c86e.svg","isPro":false,"fullname":"Eunsu Kim","user":"EunsuKim","type":"user","name":"EunsuKim"},"name":"Eunsu Kim","status":"claimed_verified","statusLastChangedAt":"2026-05-22T15:59:02.143Z","hidden":false},{"_id":"6a1054c6a53a61ce2e422fd0","name":"Jessica R. Mindel","hidden":false},{"_id":"6a1054c6a53a61ce2e422fd1","name":"Kyungjin Kim","hidden":false},{"_id":"6a1054c6a53a61ce2e422fd2","name":"Sherry Tongshuang Wu","hidden":false}],"publishedAt":"2026-05-20T00:00:00.000Z","submittedOnDailyAt":"2026-05-22T00:00:00.000Z","title":"\"I didn't Make the Micro Decisions\": Measuring, Inducing, and Exposing Goal-Level AI Contributions in Collaboration","submittedOnDailyBy":{"_id":"6576ace7769f3ee9bd7b1b88","avatarUrl":"/avatars/5b5921e54413a37afde6ce017809c86e.svg","isPro":false,"fullname":"Eunsu Kim","user":"EunsuKim","type":"user","name":"EunsuKim"},"summary":"As large language models (LLMs) increasingly shape how users form, refine, and extend their goals, attributing contributions in human-AI collaboration becomes critical for users calibrating their own reliance and for evaluators assessing AI-assisted work. Yet existing methods focus on final artifacts, missing the process through which goals themselves are jointly shaped. We introduce a goal-level attribution framework, CoTrace, that decomposes explicit goals into verifiable requirements and traces both direct contributions and indirect influences across dialogue turns. Applying CoTrace to 638 real-world collaboration logs, we find that while models account for only 11-26% of goal-shaping contribution, they contribute substantially more on introducing lower-level concrete requirements, and make various kinds of indirect contributions. Through controlled simulations, we show that interaction design choices significantly affect model goal-shaping behavior. In a user study, exposing participants to goal-level analyses shifts their perceived contributions by nearly 2 points on a 5-point scale, revealing systematic miscalibration in how users understand their own AI-assisted work.","upvotes":1,"discussionId":"6a1054c6a53a61ce2e422fd3","projectPage":"https://rladmstn1714.github.io/CoTrace/","githubRepo":"https://github.com/rladmstn1714/CoTrace","githubRepoAddedBy":"user","ai_summary":"A goal-level attribution framework called CoTrace is introduced to analyze how large language models contribute to goal shaping in human-AI collaboration, revealing that while models account for a small percentage of direct contributions, they play a significant role in introducing concrete requirements and making indirect contributions.","ai_keywords":["large language models","goal-level attribution","CoTrace","verifiable requirements","dialogue turns","human-AI collaboration","goal-shaping contribution","indirect influences","controlled simulations","user study"],"githubStars":1},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[{"_id":"6576ace7769f3ee9bd7b1b88","avatarUrl":"/avatars/5b5921e54413a37afde6ce017809c86e.svg","isPro":false,"fullname":"Eunsu Kim","user":"EunsuKim","type":"user"}],"acceptLanguages":["en"],"dailyPaperRank":0,"markdownContentUrl":"https://huggingface.co/buckets/huggingchat/papers-content/resolve/2605/2605.21363.md"}">

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