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Showing papers from Monash University, Qualcomm AI Research Show all papers

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NeurIPS 2026MonashDST GroupMonash University, Qualcomm AI RMultimodal hallucination

PAVE: Prefill-Conditioned Activation Editing for Hallucination Mitigation in LVLMs

Jingmin Zhu, Junae Kim, Dinh Phung, Trung Le 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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lenient 1/5
medium 1/10
strict 0/5
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NeurIPS 2026MonashDST GroupMonash University, Qualcomm AI RAlignment & preference optimization

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models

MATO achieves training-free multi-objective LLM alignment via test-time optimization of discovered rewards and adaptive weights during decoding, improving steerability and Pareto performance.

LINHAO LUO, Trang Vu, Van-Anh Nguyen, Junae Kim and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 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