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Showing papers from National University of Singapore (NUS) Show all papers

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Tree-Sliced Orlicz Integral Probability Metric

Tuan Hoang, Trung-Khang Tran, Viet-Hoang Tran, Tan Nguyen

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
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Conformal Prediction for Distribution-to-Distribution Regression

Trung-Khang Tran, Tuan Hoang, Viet-Hoang Tran, Tan Nguyen

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 0 of 20 reviewers recommend it
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medium 0/10
strict 0/5
86%Must read
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Change-Robust Online Topological Memory for Long-Term Relocalization and Semantic Navigation

CROSS introduces a pre-commitment localization layer using continuous SE(3) pose branches and Gaussian-mixture filtering to reject false matches, improving long-term robot relocalization and semantic navigation under severe scene changes.

Jiaming Wang, Liu Diwen, Chen Jizhuo, Atharva A Ghotavadekar 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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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5
88%Must read
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TACT: Mitigating Overthinking and Overacting in Coding Agents via Activation Steering

TACT detects overthinking and overacting as linear drift axes in hidden states and applies activation steering to pull agents back toward calibrated behavior, boosting resolution rates up to 5.8 points and cutting steps by 26%.

Yuan Sui, Yulin Chen, Yibo Li, Xue Jiang and 5 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 2/5
91%Must read
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MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome

MiroEval benchmarks multimodal deep research agents via process and outcome evaluation across 100 real-world tasks, finding process quality predicts outcomes and multimodal tasks reduce scores by 3, 10 points.

Fangda Ye, Yuxin Hu, Pengxiang Zhu, Yibo Li and 18 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 69 on Hugging Face · Code ★ 52

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17/20 AI panelreviewers recommend it

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 3/5