This work proposes a unified detection framework SAFEGuard which incorporates a hybrid fluency measurement based on cross-layer distribution distance and perplexity, and the analysis of harmful semantics through gradient matching, and demonstrates the effectiveness of SAFEGuard against evolving jailbreak attacks.
Quoc le Viet Vo, Trung Le, D. Ranasinghe et al.· 0 citations
SCALER is a coarse-to-fine forecasting framework that first employs a lightweight Transformer tailored to long-term shape modeling to predict a coarse representation of future dynamics, and reduces reliance on long description prompts, and its fixed-step refinement avoids costly reward-model-based selection, further lo...
Xuan-May Le, Minh-Tuan Tran, Ling Luo et al.· Proceedings of the 32nd ACM...· 0 citations
Long-term time series forecasting benefits from preserving global structure such as trends and seasonality. Recent LLM-based forecasters often improve accuracy through test-time scaling (e.g., iterative refinement), but these methods are computationally expensive and increasingly prone to global-shape mismatch as the p...
Xuan-May Le, Minh-Tuan Tran, Ling Luo et al.· Proceedings of the 32nd ACM...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
