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Showing papers from The University of Queensland Show all papers

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NeurIPS 2026The University of QueenslandAdelaideBaiduPekingVideo understanding

StreamMind: Dynamic Streaming Cognition for Online Video Understanding

Zhuojie Wu, Xin Shen, Chenxi Miao, Weikang Li and 3 more

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

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NeurIPS 2026The University of QueenslandELLIS Institute Finland | AaltoTU MunichAaltoDiffusion models

Directional Noise Conditioning for Diffusion Models

Mahdi Shafiei, Azade Farshad, Nassir Navab, Yousef Yeganeh

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

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NeurIPS 2026U QueenslandPohang University of Science andThe University of QueenslandChung-AngMultimodal reasoning

SeoulMMOD: A Large-Scale Multimodal Origin-Destination Flow Benchmark

Taeyoung Yu, Seonbin Jo, Jiwon Kim, Junyoung Byun

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

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NeurIPS 2026The University of QueenslandAustralian NationalAuckland University of TechnologAdelaideVision-language models

When Depth Lies: Benchmarking Vision-Language Models on Mirror-Induced RGB-D Ambiguity

HAO YIN, Tianchen Guo, Heming Du, Yan Ke and 2 more

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

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NeurIPS 2026OralU Queensland; CSIROThe University of QueenslandRMITMonashCSIRO Data61Backdoors & data poisoning

Catch-Only-One: Non-Transferable Examples for Model-Specific Authorization

Zihan Wang, Ethan Ma, Zhongkui Ma, Shuofeng Liu and 4 more

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

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NeurIPS 2026CapaloAIThe University of QueenslandEvent sequences

NOCE-Net: Representation Learning for Battery Operational Context via Nested Sequence Modelling

Arnab Bhattacharjee, Wayes Tushar, Tapan K Saha

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Institute of Science TokyoTokyo Institute of TechnologyCapital NormalBeijing Institute of TechnologyThe University of QueenslandInstruction tuning

Align Before Aggregation: Basis-Consistent Federated LoRA under Heterogeneous Ranks

Pengpeng Qiao, Yang Cao, Lingling Zhang, Guo Cheng and 4 more

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

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67%Highly rated
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NeurIPS 2026Institute of Science TokyoThe University of QueenslandTokyo Institute of TechnologyPrivacy

Rank-Aware Differentially Private Release of Listwise Preferences for LLM Alignment

Junwei Chen, Manjiang Yu, Pengpeng Qiao, Yang Cao

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

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lenient 2/5
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71%Highly rated
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NeurIPS 2026The University of QueenslandU QueenslandRL for LLMs

Block-R1: Rethinking the Role of Block Size in Multi-domain Reinforcement Learning for Diffusion Large Language Models

Block-R1 reveals domain-level block-size conflicts in diffusion LLM reinforcement learning and proposes sample-level block sizing for cross-domain post-training.

Yan Jiang, Ruihong Qiu, Zi Huang

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

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AI panel: 7 of 20 reviewers recommend it
lenient 1/5
medium 6/10
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83%Must read
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NeurIPS 2026U SouthamptonThe University of QueenslandU Electronic Science and TechnolU Illinois Urbana-ChampaignImage restoration

CHASM: Cross-frequency Harmonized Axis-Separable Mixing for Spectral Token Operators

CHASM shares a learned channel eigenbasis across frequencies while keeping frequency-specific gains, consistently improving spectral token mixers in MRI and image reconstruction.

Pengcheng Fang, Hongli Chen, Yuxia Chen, Tengjiao Sun and 2 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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AI panel: 13 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 1/5
76%Highly rated
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NeurIPS 2026The University of QueenslandSimon FraserTaobao (China) Software Co., LtdTaobao & Tmall Group of AlibAlibaba GroupVision-language models

AdaM-Rec: Adaptive Modality Routing for Multimodal Recommendation

AdaM-Rec adaptively routes between textual and visual modalities via LLM-based proxy recall tasks to improve multimodal recommendation accuracy.

Honghao Fu, Jiacheng Chen, Manxi Lin, Junjun Zheng and 6 more

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

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AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 5/10
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91%Must read
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NeurIPS 2026The University of QueenslandMonashU QueenslandMachine unlearning

Open Vocabulary Domain Unlearning

Existing domain unlearning overfits to seen classes; this paper proposes open-vocabulary domain unlearning via Fisher-masked parameter editing and targeted manifold scattering to erase domains across unseen classes with few shots.

Sumanth V Udupa, Mehrtash Harandi, Yadan Luo, Mahsa Baktashmotlagh

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

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 2/5
91%Must read
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NeurIPS 2026OralStanfordZhejiangThe University of QueenslandVision-language models

SALART-VQA: Diagnosing Whether VLMs Understand Salient Artifacts in Generated Images

SalArt-VQA evaluates VLM artifact understanding via fine-grained questions, revealing high detection recall but only 53% fully correct reasoning and a sensitivity-calibration tradeoff.

Xiaoxiao Sun, Ruotian Zhang, Junzhe Huang, James Burgess and 1 more

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

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 4/5
86%Must read
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NeurIPS 2026Harbin Institute of Technology, Harbin Institute of TechnologyThe University of QueenslandHuawei Technologies Ltd.Pengcheng LaboratoryLong-context modeling

STILL: Selecting Tokens for Intra-Layer Hybrid Attention to Linearize LLMs

STILL introduces self-saliency token selection and norm-preserved feature maps to linearize LLMs, matching original performance with up to 86.2% long-context gains.

Weikang Meng, Liangyu Huo, Yadan Luo, Jiawen Guan and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 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 4/5
medium 9/10
strict 1/5
78%Highly rated
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NeurIPS 2026The University of QueenslandProfenso Pty LtdQIMR Berghofer Medical Research U QueenslandSparse autoencoders

The Geometric Wall: Manifold Structure Predicts Layerwise Sparse Autoencoder Scaling Laws

Sparse autoencoder scaling varies by layer because curved activation manifolds with varying intrinsic dimensions impose geometry-dependent reconstruction walls rather than universal linear scaling laws.

Eslam Zaher, Maciej Trzaskowski, Quan Nguyen, Fred Roosta

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

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AI panel: 11 of 20 reviewers recommend it
lenient 3/5
medium 6/10
strict 2/5
71%Highly rated
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NeurIPS 2026Macau University of Science and Macau University of Science and The University of QueenslandNational University of SingaporeInstitute of automation, Chinese3D vision & reconstruction

Marrying Optimal Transport and ODEs for Unified Continuous-Time 4D Reconstruction and Tracking

Uni4R unifies continuous-time 4D reconstruction and tracking via optimal-transport and ODE velocity fields, achieving state-of-the-art results on both tasks and continuous-time kinematics benchmarks.

Liying Yang, Hao Mo, Jialun Liu, Chen Liu and 6 more

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

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AI panel: 6 of 20 reviewers recommend it
lenient 2/5
medium 4/10
strict 0/5