Showing papers from University of California, Riverside 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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Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
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CLIOPATRA attacks privacy-preserving LLM insight platforms with malicious chats to leak target medical histories with nearly 100% precision in 65% of cases, showing layered heuristic protections are insufficient.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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RefGRPO closes LLM agents' reflection gap via a free calibration bonus and dynamic schedule, improving calibration and task accuracy. Calibrated reflections enable self-improvement without outcome supervision and effective selective prediction.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Discrete stochastic localization uses unit-sphere embeddings with SNR-invariant denoisers to enable flexible continuous-state non-autoregressive generation with improved fidelity and hybrid sampling.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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A unified framework combines unsupervised pretraining and supervised neural knowledge graph learning, with a nonasymptotic risk bound showing unlabeled data reduces downstream prediction error.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Removing hindsight relabeling enables stable pure-RL online finetuning of Decision Transformers via adapted GRPO with sub-trajectory optimization and active sampling, achieving state-of-the-art results.
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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MT-JailBench provides a modular framework for comparing multi-turn jailbreak attacks under standardized conditions, finding that prompt generation drives success and recomposed components yield stronger attacks.
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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