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Showing Synthetic data Show all papers

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NeurIPS 2026MITSynthetic data

Dataset Distillation via Drifting

George Cazenavette, Angelina Quan, Giannis Daras, Antonio Torralba and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Opt-Arena: Evaluating, Selecting, and Generating Optimization Modeling Data via Tripartite Graphs

Yian Xu, Xiongwei Han, Jie Wang, Haoyang Liu and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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57%Worth a look
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Firefly: Illuminating Verified Real-world Tool Call Data Generation

Yuxuan Lu, Ziyi Wang, Yingzhou Lu, Yisi Sang and 11 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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86%Must read
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DD-Ranking: Rethinking the Evaluation of Dataset Distillation

DD-Ranking reveals dataset distillation gains come from extra evaluation techniques rather than image quality, proposing fair metrics to assess true synthetic dataset value.

Zekai Li, Xinhao Zhong, Samir Khaki, Zhiyuan Liang and 36 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5
72%Highly rated
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Epiplexity Guided Data Selection and Generation for Out-of-Distribution Generalization

Epiplexity guides data selection and synthetic generation to improve out-of-distribution transfer by favoring structurally rich training data.

Ellen Su, Andres Potapczynski, Shikai Qiu, Edward Hughes and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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8/20 AI panelreviewers recommend it

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AI panel: 8 of 20 reviewers recommend it
lenient 4/5
medium 4/10
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