Showing papers from University of Melbourne Show all papers
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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PhysGuard uses Fisher-guided gradient projection to adapt neural PDE surrogates to real data while preserving physics-critical parameters, cutting low-frequency error by up to 32% under severe domain shift.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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BETA uses a local steering model and prediction harmonization to stabilize black-box test-time adaptation with zero extra API queries and large accuracy gains.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Using input-to-state stability, zeroth-order optimization achieves first-order convergence rates without extra dimension dependence when perturbations are small.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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RAIL introduces a CHC-based benchmark evaluating LALMs across five auditory cognitive abilities, revealing highly uneven performance among 26 state-of-the-art models.
Published 2026 · ▲ 5 on Hugging Face
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VEX-Bench benchmarks verification complexity of LLM-generated misinformation, showing high-VEX false content costs 3-169x less to create than to verify and risks misallocating scarce screening resources.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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SVoT uses reinforcement learning to generate verifiable intermediate states and visualizations for multi-hop spatial reasoning, achieving up to 65% out-of-distribution accuracy gains.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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CELEUS uses E-processes with uncertainty-guided sampling and surrogate approximations to provide anytime-valid confidence intervals for LLM evaluation, cutting required samples by 54-62%.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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