Cover Image

Hogwild! Inference: Parallel LLM Generation via Concurrent Attention

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rodionov, Gleb, Garipov, Roman, Shutova, Alina, Yakushev, George, Schultheis, Erik, Egiazarian, Vage, Sinitsin, Anton, Kuznedelev, Denis, Alistarh, Dan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models
by: Shutova, Alina, et al.
Published: (2025)

Extreme Compression of Large Language Models via Additive Quantization
by: Egiazarian, Vage, et al.
Published: (2024)

Grid Games: The Power of Multiple Grids for Quantizing Large Language Models
by: Egiazarian, Vage, et al.
Published: (2026)

Evaluating Memory Structure in LLM Agents
by: Shutova, Alina, et al.
Published: (2026)

Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization
by: Egiazarian, Vage, et al.
Published: (2024)

Asynchronous Reasoning: Training-Free Interactive Thinking LLMs
by: Yakushev, George, et al.
Published: (2025)

WUSH: Near-Optimal Adaptive Transforms for LLM Quantization
by: Chen, Jiale, et al.
Published: (2025)

LLMQ: Efficient Lower-Precision Pretraining for Consumer GPUs
by: Schultheis, Erik, et al.
Published: (2025)

AutoJudge: Judge Decoding Without Manual Annotation
by: Garipov, Roman, et al.
Published: (2025)

EvoPress: Accurate Dynamic Model Compression via Evolutionary Search
by: Sieberling, Oliver, et al.
Published: (2024)

Quartet II: Accurate LLM Pre-Training in NVFP4 by Improved Unbiased Gradient Estimation
by: Panferov, Andrei, et al.
Published: (2026)

Bridging the Gap Between Promise and Performance for Microscaling FP4 Quantization
by: Egiazarian, Vage, et al.
Published: (2025)

Unified Scaling Laws for Compressed Representations
by: Panferov, Andrei, et al.
Published: (2025)

Reasoning Shift: How Context Silently Shortens LLM Reasoning
by: Rodionov, Gleb
Published: (2026)

The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information
by: Wu, Diyuan, et al.
Published: (2024)

PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression
by: Malinovskii, Vladimir, et al.
Published: (2024)

Talking Trees: Reasoning-Assisted Induction of Decision Trees for Tabular Data
by: Yakushev, George, et al.
Published: (2025)

DASH: Faster Shampoo via Batched Block Preconditioning and Efficient Inverse-Root Solvers
by: Modoranu, Ionut-Vlad, et al.
Published: (2026)

Graph Neural Networks Gone Hogwild
by: Solodova, Olga, et al.
Published: (2024)

Neural Optimal Transport with General Cost Functionals
by: Asadulaev, Arip, et al.
Published: (2022)

Discrete Neural Algorithmic Reasoning
by: Rodionov, Gleb, et al.
Published: (2024)

FFT-based Dynamic Subspace Selection for Low-Rank Adaptive Optimization of Large Language Models
by: Modoranu, Ionut-Vlad, et al.
Published: (2025)

MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models
by: Frantar, Elias, et al.
Published: (2024)

Switti: Designing Scale-Wise Transformers for Text-to-Image Synthesis
by: Voronov, Anton, et al.
Published: (2024)

Rethinking Optimal Transport in Offline Reinforcement Learning
by: Asadulaev, Arip, et al.
Published: (2024)

Are LLMs classical or nonmonotonic reasoners? Lessons from generics
by: Leidinger, Alina, et al.
Published: (2024)

Position: It's Time to Act on the Risk of Efficient Personalized Text Generation
by: Iofinova, Eugenia, et al.
Published: (2025)

Speculative Decoding Speed-of-Light: Optimal Lower Bounds via Branching Random Walks
by: Pankratov, Sergey, et al.
Published: (2025)

Simple Opinion Dynamics for No-Regret Learning
by: Lazarsfeld, John, et al.
Published: (2023)

Behemoth: Benchmarking Unlearning in LLMs Using Fully Synthetic Data
by: Iofinova, Eugenia, et al.
Published: (2026)

Model Compression with Exact Budget Constraints via Riemannian Manifolds
by: Helcig, Michael, et al.
Published: (2026)

MatryoshkaLoRA: Learning Accurate Hierarchical Low-Rank Representations for LLM Fine-Tuning
by: Modoranu, Ionut-Vlad, et al.
Published: (2026)

Apertus LLM Family Expansion via Distillation and Quantization
by: Panferov, Andrei, et al.
Published: (2026)

Catching the context: the first genre-determined reading of Francysk Skaryna’s portrait
by: Olga Shutova
Published: (2022)

How do languages influence each other? Studying cross-lingual data sharing during LM fine-tuning
by: Choenni, Rochelle, et al.
Published: (2023)

Does Diffusion Beat GAN in Image Super Resolution?
by: Kuznedelev, Denis, et al.
Published: (2024)

Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond
by: Platonov, Oleg, et al.
Published: (2022)

Generating artificial digital image correlation data using physics-guided adversarial networks
by: Melching, David, et al.
Published: (2023)

Key Algorithms for Keyphrase Generation: Instruction-Based LLMs for Russian Scientific Keyphrases
by: Glazkova, Anna, et al.
Published: (2024)

LitmusKt: Concurrency Stress Testing for Kotlin
by: Lochmelis, Denis, et al.
Published: (2025)