Tag: #v1120 results
Dual-stream unsupervised model fuses anomaly detection with physics proxies for embedded vehicle monitoring. Distinguishes transient shocks from sustained high-load states like hill climbing. Runs efficiently on RISC-V ECUs.
Presents Physics-Enhanced Swin Transformer (PEST) for 3D turbulence. Uses windowed attention, frequency loss, and physics constraints. Outperforms baselines in accuracy and stability.
PELLI is an iterative framework for integrating LLMs into software generation, evaluating code on maintainability, performance, and reliability. It tests five popular LLMs across three domains using Python standards. GPT-4T and Gemini outperform others, with prompt design impacting quality.
Calliope creates synchronized narrated EPUB3 e-books from text using open-source TTS like XTTS-v2. Ensures exact audio-text sync via direct timestamps, preserves original layout offline. Avoids cloud privacy and cost issues.
OmniVL-Guard unifies vision-language forgery detection and grounding with balanced RL. Self-Evolving CoT and ARSPO tackle difficulty bias. Excels in zero-shot generalization.
NSAM learns symbolic models and action masks automatically during DRL to avoid infeasible actions. It integrates symbolic reasoning with deep policy optimization mutually. Evaluations show improved sample efficiency and fewer violations.
White paper integrates nonuniform ellipticity breakthrough with topos-theoretic LRMs. Formalizes sharp Schauder estimates using ghost equations. Enables autonomous proofs in calculus of variations.
Neural Additive Experts use mixture-of-experts per feature with context-gated integration for flexible additivity. Targeted regularization ensures smooth transitions from additive to interactive models. Outperforms on accuracy while preserving feature explanations.
SecureScan uses logistic regression, heuristics, and VirusTotal for URL/file/binary triage. Achieves 93.1% accuracy with balanced precision/recall. Employs gray-zone logic to cut false positives.
MalMoE detects encrypted malicious traffic using graph-based Mixture-of-Experts to handle graph drift. It selects optimal 1-hop-GNN experts via a redesigned gate model. Trained with two-stage strategy and augmentation for real-time precision.