Showing papers from Qualcomm Inc, QualComm Show all papers
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 5, Thu, Dec 10, 10:00 AM–1:00 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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Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · 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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Conditional Information Bottleneck frames reasoning as lossy compression with a semantic surprisal prior, improving LLM reasoning efficiency with minimal accuracy loss.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 23 on Hugging Face
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MAPLE trains vision-language-action driving models via latent multi-agent rollout and reinforcement learning, achieving state-of-the-art closed-loop performance without external simulators.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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GeRo enables vision-language-action models to generate language-grounded future traffic scenes via autoregressive rollouts, improving Bench2Drive driving scores by 15.7 and success rates by 26.2.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Kernelized Activation Steering lifts activation steering into a reproducing kernel Hilbert space to induce locally adaptive, geometry-aware steering via implicit kernel evaluations, recovering Difference-in-Means as a linear special case and outperforming standard methods on LLM and image control ta
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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A unified meta-learning framework minimizes decomposed risk bounds across marginal and conditional distribution shifts to achieve robust domain generalization. It achieves state-of-the-art results on standard benchmarks and challenging multi-domain long-tailed recognition settings.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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