3 papers
cs.LG2026
ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models
Adrien Schoen, Nachiketa Ratnakar Patil, Arjun Bhagoji +1
Modern sequence models, from Transformers to State Space Models, have enabled powerful generative modeling across diverse domains, yet they are typically trained to predict what ha…
cs.NI2026
NetSSM: Multi-Flow and State-Aware Network Trace Generation using State Space Models
Andrew Chu, Xi Jiang, Shinan Liu +4
Access to raw network traffic data is essential for many computer networking tasks, from traffic modeling to performance evaluation. Unfortunately, this data is scarce due to high…
cs.NI2024
Beyond Data Points: Regionalizing Crowdsourced Latency Measurements
Taveesh Sharma, Paul Schmitt, Francesco Bronzino +2
Despite significant investments in access network infrastructure, universal access to high-quality Internet connectivity remains a challenge. Policymakers often rely on large-scale…