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NeurIPS 2026RMITRMITRoyal Melbourne Institute of TecMonashU MelbourneMachine unlearning

What Should Remain After Forgetting? Rethinking LLM Unlearning as Predictive Posterior Correction

Jingyue Cong, Andy Song, Alexis Horde-Vo, Kai Wei and 4 more

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

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lenient 1/5
medium 1/10
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67%Highly rated
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NeurIPS 2026Royal Melbourne Institute of TecRMITHallucination & factuality

Why Are LLMs Confidently Wrong? Correcting Overconfident Errors via Causal Head Intervention

Jing Ren, Bowen Li, Ziqi Xu, Xuechao Yang and 1 more

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

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45%Niche pick
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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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91%Must read
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NeurIPS 2026Royal Melbourne Institute of TecRMITU MelbourneJilinNanyang TechnologicalMechanistic interpretability

The Commit-Abstain Circuit: Why Language Models Hallucinate Instead of Abstaining

Mechanistic analysis reveals a Commit-Abstain Circuit where early commitment signals overpower later abstention corrections, causing hallucinations; training on its activations improves abstention accuracy by 12.2 points.

Gavin Vy Nguyen, Ziqi Xu, Jeffrey Chan, Estrid He 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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AI panel: 17 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 4/5
83%Must read
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NeurIPS 2026JilinAdelaideRMITJinanRoyal Melbourne Institute of TecDynamic graphs

UFO: A Unified Flow-Oriented Framework for Robust Continual Graph Learning

UFO proposes a flow-oriented continual graph learning framework that combats catastrophic forgetting and noisy-label-induced catastrophic remembering via generative replay and instance reliability scoring, outperforming baselines across benchmarks.

Danhui Zhang, Zhe Wang, Qing Qing, Jiarui Liu and 5 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · 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 8/10
strict 0/5