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Can Large Language Models Develop Gambling Addiction?

Seungpil Lee, Donghyeon Shin, Yunjeong Lee, Sundong Kim

Sydney Poster Session 1, Tue, Dec 8, 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
76%Highly rated
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ComPose: When to Trust Hands for Object Pose Tracking

ComPose tracks 6DoF object pose in RGB video by using hand motions as complementary cues, achieving robust accuracy under severe occlusion without external priors.

Jisu Shin, Junoh Lee, JunGyu Lee, Inhwan Bae 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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10/20 AI panelreviewers recommend it

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AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 0/5
71%Highly rated
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Why Learning Rediscovers the Closed-Form Diagonal Regularizer

Diagonal regularizers saturate at a prior-driven power law because isotropic truncation noise and eigenvalue counting yield flat loss landscapes, so learned diagonal forms barely beat the closed form and only cross-mode coupling enables real gains.

Jeahn Han, Pyojin Kim

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

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7/20 AI panelreviewers recommend it

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AI panel: 7 of 20 reviewers recommend it
lenient 2/5
medium 4/10
strict 1/5
78%Highly rated
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Hide to See: Reasoning-prefix Masking for Visual-anchored Thinking in VLM Distillation

A reasoning-prefix masking framework distills think-answer visual reasoning into compact VLMs by masking salient reasoning cues to force visual anchoring, improving multimodal benchmarks over prior distillation methods.

Seonghoon Yu, Dongjun Nam, Byung-Kwan Lee, Jeany Son

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

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 0/5
78%Highly rated
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Rebalancing Reference Frame Dominance to Improve Motion in Image-to-Video Models

DyMoS rebalances reference-frame self-attention in image-to-video models to boost motion dynamics without retraining or altering inputs.

Wooseok Jeon, Seungho Park, Seunghyun Shin, Sangeyl Lee and 2 more

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

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AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 0/5
86%Must read
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From Noise to Diversity: Random Embedding Injection in LLM Reasoning

Random soft prompt injection boosts LLM math reasoning by flattening early token distributions to diversify reasoning paths and widen Pass@N without any training.

Heejun Kim, Seungpil Lee, Jewon Yeom, Jaewon Sok and 4 more

Sydney Poster Session 2, Tue, Dec 8, 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