From the 1 of 28 linked papers with an AI index.
9 papers · 1 filter
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…
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…
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-…
Revisiting Adaptive Rounding with Vectorized Reparameterization for LLM Quantization
Yuli Zhou, Qingxuan Chen, Luca Benini +2
Adaptive Rounding has emerged as an alternative to round-to-nearest (RTN) for post-training quantization by enabling cross-element error cancellation. Yet, dense and element-wise r…
LUNA: Efficient and Topology-Agnostic Foundation Model for EEG Signal Analysis
Berkay Döner, Thorir Mar Ingolfsson, Luca Benini +1
Electroencephalography (EEG) offers a non-invasive lens into human brain activity, but building large-scale models is hampered by topological heterogeneity: each public EEG data de…