From the 1 of 27 linked papers with an AI index.
27 papers
S-CEReBrO: Breaking the Memory Barrier in Continuous EEG Monitoring
Glenn Anta Bucagu, Thorir Mar Ingolfsson, Yawei Li +1
The paper introduces S-CEReBrO, a streaming Transformer architecture that uses a windowed alternating attention mechanism to keep memory usage constant during continuous EEG monito…
One Shot vs. Iterative: Rethinking Pruning Strategies for Model Compression
MikoÅaj Janusz, Tomasz Wojnar, Yawei Li +2
Pruning is a core technique for compressing neural networks to improve computational efficiency. This process is typically approached in two ways: one-shot pruning, which involves…
Gated Relational Alignment via Confidence-based Distillation for Efficient VLMs
Yanlong Chen, Amirhossein Habibian, Luca Benini +1
Vision-Language Models (VLMs) achieve strong multimodal performance but are costly to deploy, and post-training quantization often causes significant accuracy loss. Despite its pot…
Quantizing Recursive Reasoning Models
Thorir Mar Ingolfsson, Wajeeha Tahir, Anna Tegon +3
Recursive reasoning models solve hard puzzles by applying compact, weight-tied blocks over many refinement steps. Because these blocks are reused many times, quantizing them create…
LuMamba: Latent Unified Mamba for Electrode Topology-Invariant and Efficient EEG Modeling
Danaé Broustail, Anna Tegon, Thorir Mar Ingolfsson +2
Electroencephalography (EEG) enables non-invasive monitoring of brain activity across clinical and neurotechnology applications, yet building foundation models for EEG remains chal…
RDKV: Rate-Distortion Bit Allocation for Joint Eviction and Quantization of the KV Cache
Junkai Zhang, Hang Guo, Luca Benini +1
Large language models (LLMs) have shown strong performance across diverse tasks, but their inference with long input contexts is bottlenecked by memory size and bandwidth. The Key-…