Beyond [SEG] Tokens: Training-Free Video Reasoning Segmentation via Counterfactual Inference and Contrastive Concept

Tianlu Zhang, guiguang ding, Jungong Han

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

Trajectory-Consistent Diffusion Policies for Offline Reinforcement Learning

Yichao Fu, Shangde Gao, Zhuoling Li, Wen Wang and 2 more

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

When Does Trimming Help Conformal Prediction? A Retained-Law Diagnostic under Calibration Contamination

Congye Wang

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

Look Before You Leap: Self-Evolving Clinical Reasoning with Psychometric Preference Optimization for Radiology Report Generation

Qi Wang, Yunfeng Min, Liwei Huang, Zeyu Zhang and 2 more

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

CofactVLA: Deconfounding Vision-Language-Action Models via Counterfactual Intervention

CofactVLA deconfounds vision-language-action models via counterfactual intervention to eliminate visual confounders and boost out-of-distribution success by 52.3%.

Yan Zhang, Yinan Wu, Haoran Duan, Jungong Han

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

Active Learning for Gaussian Process Regression Under Self-Induced Boltzmann Weights

AB-SID-iVAR actively learns Gaussian process targets under unknown self-induced Boltzmann weights, achieving vanishing terminal prediction error without partition function estimation.

Jixiang Qing, Henry Moss, Matthias Sachs

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

NDPP-Grasp: Non-Differentiable Physical Plausibility Constraint-Guided Task-Oriented Dexterous Grasp Generation

NDPP-Grasp injects non-differentiable physical plausibility guidance into grasp diffusion denoising, improving task-oriented dexterous grasp physical plausibility while preserving alignment.

Qiuchi Xiang, Haoxuan Qu, Hossein Rahmani, Jun Liu

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

Conditioning Gaussian Processes on Almost Anything

Gaussian processes are recast as linear diffusion models to enable conditioning on arbitrary likelihoods, including language and physics, via ODE sampling without bespoke derivations.

Henry Moss, Lachlan Astfalck, Tom Cowperthwaite, Colin Doumont and 4 more

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

Tempered Guided Diffusion

Tempered Guided Diffusion uses annealed sequential Monte Carlo to concentrate computation on plausible diffusion trajectories, improving posterior approximation and speed-quality tradeoffs versus independent guided sampling.

Andreas Makris, Paul Fearnhead, Christopher Nemeth

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

PhaseLoRA: Control-Regime-Conditioned Low-Rank Adaptation for Continuous-Action Vision-Language-Action Policies

PhaseLoRA conditions LoRA updates on control-regime descriptors at each step, improving continuous-action VLA success by 12.2 points over high-rank baselines.

Yufei Guo, Yinan Wu, Haoran Duan, guiguang ding and 1 more

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