LLM Compression by Block Removal with Constrained Binary Optimization
cs.LG, cs.AI, cs.CL, quant-ph
Submitted: 2026-01-29
Updated: 2026-09-11
Comments: 16 pages, 3 figures
Code: https://github.com/CompactifAI/Block_removal_through_constrained_
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- A Full-Stack Platform Architecture for Self-Organised Social Coordination
- Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
- Sliding-Window Merging for Compacting Patch-Redundant Layers in LLMs
- A Quantum Approximate Optimization Algorithm
- GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
- Measuring Massive Multitask Language Understanding
- AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
- The Llama 3 Herd of Models
- Ministral 3
- GPT-4 Technical Report
- Globally optimized SVD compression of LLMs via Fermi-function-based rank selection and gauge fixing
- Scalable iterative pruning of large language and vision models using block coordinate descent
- WinoGrande: An Adversarial Winograd Schema Challenge at Scale
- Compact Language Models via Pruning and Knowledge Distillation
- A Simple and Effective Pruning Approach for Large Language Models
- Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
- ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models
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