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Showing papers from University of Houston Show all papers

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The Power of a Random Sample in Online Algorithms

Omer Wasim, Sami Davies, Shallu Tomer, Rathish Das

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

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57%Worth a look
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FairTune Market: A Fair and Trustworthy Marketplace for Fine-Tuned LLMs via Posted-Price & Proper-Scoring Mechanisms

Jiachen Shen, Xingke Yang, Hui Zhong, Aohan Li and 4 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
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Efficient Collaborative LLM Fine-Tuning over Heterogeneous Mobile Devices via Many Backbones to One Side-Network Tuning

Xingke Yang, Liang Li, Sicong Li, Liwei Guan and 5 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
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medium 0/10
strict 0/5
57%Worth a look
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From Generic to Dedicated: A Novel Optimizer for Online Continual Learning

Yongyi Wu, Zheng Wang, Sen Lin

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

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
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UniReFP: Robust Unified Fingerprinting for Vision Models against Cross-Task Repurposing Attacks

Ziye Geng, Guang Yang, Yihang Chen, Lingfeng Yao and 4 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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Specialists Hold, Generalists Discount: Asymmetric Equilibrium in LLM Routing Auctions

Xinyu Hou, Yang Lu, Rabimba Karanjai, Pei-Chi Pan and 3 more

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

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Robust Surrogate Modeling for Explainable Graph Neural Networks

Zhuomin Chen, Jingchao Ni, Hojat Allah Salehi, Xu Zheng 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
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Online Allocation with Differential Privacy

Jianyi Yang, Xingyu Zhou, Mostafa Mushsharat, Shaolei Ren

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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78%Highly rated
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Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention

Stochastic Attention randomizes attention weights at inference to generate calibrated predictive ensembles without retraining, achieving best native calibration with minimal tuning cost.

Akash Yadav, Taiwo Adebiyi, Ruda Zhang

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5