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Modeling quantum neural network gradient with reinforcement learning

RLQ-Grad uses reinforcement learning to propose quantum neural network updates without differentiating circuits, avoiding barren plateaus and scaling with parameters rather than Hilbert space dimension to achieve orders-of-magnitude faster training and higher accuracy.

Nhan Luu, Trung D Luu, Ngoc Nam Pham, Thang C Truong

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

100% Readers1 of 1 upvoted
15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 3/5
45%Niche pick
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Trajectory-Matching Meta Pseudo-Labeling for Semi-Supervised Learning

Minh Duc Le, Minh-Duong Nguyen, Dung Le

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

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AI panel: 0 of 20 reviewers recommend it
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45%Niche pick
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How Finite-Rank Bottleneck Shape the Low-Rank Adaptation Landscape

Long Nguyen-Chi, Quynh Nguyen, Thanh Nguyen Cung, Binh T. Nguyen

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

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57%Worth a look
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Birth-Death Structural Learning for 3D Gaussian Splatting

Tran Hong Quan, Long Nguyen-Chi, Binh T. Nguyen

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

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1/20 AI panelreviewers recommend it

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
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Benchmarking Vietnamese Legal Knowledge of Large Language Models

Dong N Tien, Nguyen Minh-Anh, Thanh D Hoang, Nguyen T Ngoc and 5 more

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

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AI panel: 1 of 20 reviewers recommend it
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74%Highly rated
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MulCLIP: A Multi-level Alignment Framework for Enhancing Fine-grained Long-context CLIP

MulCLIP aligns images with long captions via multi-level token and patch strategies, improving fine-grained vision-language understanding without region proposals.

Chau Truong, Hieu Ta, Zhenzhen Liu, Dung Le

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

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 0/5
91%Must read
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HERO: A Heterogeneity-Aware Benchmark Library for Federated Continual Learning

HERO introduces a heterogeneity-aware benchmark library for federated continual learning that separates task splits, client splits, and sequences to expose hidden performance disparities.

Thinh Nguyen, Le-Tuan Nguyen, Minh-Duong Nguyen, Nhi Trinh 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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17/20 AI panelreviewers recommend it

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AI panel: 17 of 20 reviewers recommend it
lenient 4/5
medium 10/10
strict 3/5
91%Must read
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Rethinking Molecular Graph Backdoors under Chemistry-aware Admission

ChemGuard exposes that chemistry-aware admission invalidates many molecular graph backdoors, but ChemBack achieves high attack success with fully admitted poisons via chemically feasible motif-anchor attachments.

Thinh Nguyen, Sze Jue Yang, Khoa D Doan, Chee Seng Chan and 1 more

Sydney Poster Session 2, Tue, Dec 8, 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 9/10
strict 3/5
83%Must read
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Nonparametric Distribution Matching for Self-Supervised Whole-Slide Image Condensation

NICER reformulates whole-slide image condensation as nonparametric distribution matching, improving self-supervised learning accuracy by 7.44% over heuristic methods.

Duong Nguyen, Nghia Hoang, Hang T Nguyen, Thanh Trung Huynh and 2 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 2/5
80%Must read
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Latent Abstraction for Retrieval-Augmented Generation

LAnR unifies RAG by using a single LLM's latent space for dense retrieval and adaptive stopping, outperforming existing methods with fewer retrieval calls.

Thi Ha Lan Nguyen, Nguyen Minh-Anh, Dung Le

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

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 0/5
83%Must read
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Decoding the Critique Mechanism in Large Reasoning Models

Large reasoning models use hidden critique abilities to recover from uncorrected reasoning errors, and steering with critique vectors improves error detection and test-time scaling without training.

Hoang Phan, Nguyen Hung-Quang, Thanh Quoc Hung Le, Xiusi Chen and 2 more

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

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AI panel: 13 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 2/5
86%Must read
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BSO: Safety Alignment Is Density Ratio Matching

BSO recasts safety alignment as density ratio matching via Bregman divergence minimization, yielding a single-stage loss that improves the safety-helpfulness trade-off without auxiliary models.

Tien-Phat Nguyen, Truong Nguyen, Thin Nguyen, Duy M. H. Nguyen 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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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 2/5