3 papers
cs.LG2026
APreQEL: Adaptive Mixed Precision Quantization For Edge LLMs
Meriem Bouzouad, Yuan-Hao Chang, Jalil Boukhobza
Today, large language models have demonstrated their strengths in various tasks ranging from reasoning, code generation, and complex problem solving. However, this advancement come…
cs.LG2026
RETENTION: Resource-Efficient Tree-Based Ensemble Model Acceleration with Content-Addressable Memory
Yi-Chun Liao, Chieh-Lin Tsai, Yuan-Hao Chang +3
Although deep learning has demonstrated remarkable capability in learning from unstructured data, modern tree-based ensemble models remain superior in extracting relevant informati…
cs.DC2025
A retrospective on DISPEED -- Leveraging heterogeneity in a drone swarm for IDS execution
Vincent Lannurien, Camélia Slimani, Louis Morge-Rollet +4
Swarms of drones are gaining more and more autonomy and efficiency during their missions. However, security threats can disrupt their missions' progression. To overcome this proble…