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UrgenT Help Detecting Performance Regressions Using Machine Learning and Hardware Counters [P]
A Reddit user seeks community advice on methodological best practices for one-class anomaly detection in performance regression testing using hardware counters, with limited healthy-sample data.
Aug 14, 2026
ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models
ChronoSSM is a new autoregressive State Space Model that jointly trains on both event tokens and timestamps to improve temporal reasoning in sequence modeling, addressing a gap where timing is typically treated as secondary to event prediction.
Aug 12, 2026
Optimizing Transformer Neural Network for Real-Time Outlier Detection on FPGAs
Researchers propose an FPGA-optimized Transformer architecture for real-time financial time-series outlier detection, aiming to improve speed and stability of downstream data processing.
Jul 28, 2026
IonSense-QKG: A Quantum-Readiness Metadata Framework for Lithium-Ion Battery Dataset Discovery
IonSense-QKG is a metadata framework that adds quantum-readiness attributes to public lithium-ion battery datasets to help researchers identify which datasets are technically suitable for near-term hybrid quantum-classical ML workflows.
Published Jul 3, 2026 · Analyzed Jul 6, 2026