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NeurIPS 2026SpotlightHigher School of EconomicsInstitute of Science and TechnolIST AustriaAril ComputerETH ZurichQuantization

Grid Games: The Power Of Multiple Grids for Quantizing Large Language Models

Multiple grids per group improve 4-bit quantization by selecting better grids per group, consistently boosting accuracy over single-grid FP4 for weights and activations.

Vage Egiazarian, Erik Schultheis, Andrei Panferov, Earl Killian and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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lenient 4/5
medium 7/10
strict 0/5
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NeurIPS 2026Massachusetts Institute of TechnComputer Science and Artificial IST Austria & NeuralMagicIBM ResearchMIT/NeuralmagicPruning & sparsity

The Sparsity Whisperer

Difference-informed pruning preserves output differences via difference-aware weight scoring, improving LLM sparsity over activation and reconstruction baselines at minimal cost.

Linghao Kong, Inimai Subramanian, Micah Adler, Dan Alistarh and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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17/20 AI panelreviewers recommend it

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 2/5