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Showing papers from Computer Science and Engineering Department, University of California, San Diego Show all papers

45%Niche pick
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(Strongly) Replicable Distribution Testers imply High Probability Distribution Testers

Ilias Diakonikolas, Jingyi Gao, Daniel Kane, Sihan Liu and 1 more

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

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AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
67%Highly rated
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sMMC-22M: A Context-Aware Dataset and Benchmark for Single-Cell Spatial Transcriptomics

Xi Li, Yaqi Hu, Ziheng Duan, Xinyi Wang and 4 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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2/20 AI panelreviewers recommend it

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AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
76%Highly rated
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Measuring What Matters: Synthetic Benchmarks for Concept Bottleneck Models

Synthetic benchmarks for concept bottleneck models generate controlled labeled datasets to evaluate decision support and automation use cases, diagnose failure modes, and guide testing.

Julian Skirzynski, Harry Cheon, Shreyas Kadekodi, Meredith Stewart and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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10/20 AI panelreviewers recommend it

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AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 1/5
72%Highly rated
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Testable Learning of General Halfspaces under Massart Noise

A testable learning algorithm learns general Massart halfspaces under Gaussian marginals with quasi-polynomial complexity matching SQ lower bounds.

Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane, Sihan Liu

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · 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 2/5
medium 4/10
strict 2/5