Pruning LLMs Like a Physicist: Block Removal as an Ising Optimization Problem

Local-Minima-Preserving Continuous Relaxation of Ising Problems

arXiv:2606. 30333v1 Announce Type: cross Abstract: The generalized Ising problem captures a broad spectrum of hard combinatorial problems, including MAX-CUT, Number Partitioning (NPP), and Maximum Independent Set.

LLM Compression by Block Removal with Constrained Binary Optimization

arXiv:2602. 00161v2 Announce Type: replace-cross Abstract: In this paper, we formulate the compression of large language models (LLMs) by optimally deleting transformer blocks (``block removal'') as a constrained binary optimization (CBO) problem that can be mapped to a physical system (Ising glass), whose energies are a strong proxy for downstream model performance.

Preference Tuning LLMs with Direct Preference Optimization Methods

Optimizing your LLM in production

Fine-tuning LLMs to 1.58bit: extreme quantization made easy

A Fast and Effective Method for Euclidean Anticlustering: The Assignment-Based-Anticlustering Algorithm

arXiv:2601. 06351v2 Announce Type: replace Abstract: Anticlustering is an NP-hard combinatorial optimization problem that consists of partitioning a set of objects into equal-sized groups called anticlusters such that the objects in the same anticluster are as dissimilar as possible and thereby representative of the entire set of objects.