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cs.LG2026
MACaQ: Fast, Model Agnostic Calibrated Quantization for Low-Precision Weights and Activations
Lorenz K. Muller, Philippe Bich, Chiara Boretti +3
Weight-activation quantization can reduce the memory and compute cost of neural-network inference, but recent methods often require expensive optimization and architecture-specific…
cs.LG2026
KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks
Lorenz K. Muller, Philippe Bich, Chiara Boretti +3
Test-time scaling is a powerful approach to obtain better reasoning in large language models, but it becomes memory-bottlenecked during long-horizon decoding, as the KV-cache grows…