Torsten Hoefler
21 papers · 2018–2026 · 11 venues · across top CS/AI venues
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(95)
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Venues
Top co-authors
Research topics
Machine Learning
(16)
Artificial Intelligence
(11)
Deep Learning
(11)
Core AI
(10)
Application Areas
(7)
Core Methods
(5)
Optimization & Theory Β· Machine Learning
(5)
Techniques
(5)
Natural Language Processing
(3)
Architectures
(3)
Learning Types
(3)
Optimization & Theory Β· Deep Learning
(3)
Resources & Methods
(3)
Computer Science
(2)
Mathematics & Optimization
(2)
Keywords
model compression
(4)
large language model
(3)
neural network pruning
(2)
stochastic gradient descent
(2)
weight quantization
(2)
4-bit quantization
(2)
model selection
(1)
semantic representation
(1)
model quantization
(1)
neural architecture search
(1)
diffusion model
(1)
efficient inference
(1)
graph representation
(1)
parameter sharing
(1)
distributed learning
(1)
program analysis
(1)
weather prediction
(1)
semantic analysis
(1)
distributed training
(1)
data compression
(1)
Papers
Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
ACL 2026
All models are wrong, some are useful: Model Selection with Limited Labels
AISTATS 2025
A High-Performance Design, Implementation, Deployment, and Evaluation of The Slim Fly Network
NSDI 2024
DiffDA: a Diffusion model for weather-scale Data Assimilation
ICML 2024
Graph of Thoughts: Solving Elaborate Problems with Large Language Models
AAAI 2024
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
NeurIPS 2024
QUIK: Towards End-to-end 4-Bit Inference on Generative Large Language Models
EMNLP 2024
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
ICLR 2024
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression
ICLR 2024
Swing: Short-cutting Rings for Higher Bandwidth Allreduce
NSDI 2024
Compressing multidimensional weather and climate data into neural networks
ICLR 2023
Differentiable Transportation Pruning
ICCV 2023
OPTQ: Accurate Quantization for Generative Pre-trained Transformers
ICLR 2023
ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts
NeurIPS 2022
Neural Parameter Allocation Search
ICLR 2022
Spatial Mixture-of-Experts
NeurIPS 2022
ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations
ICML 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
JMLR 2021
Augment Your Batch: Improving Generalization Through Instance Repetition
CVPR 2020
Neural Code Comprehension: A Learnable Representation of Code Semantics
NeurIPS 2018
The Convergence of Sparsified Gradient Methods
NeurIPS 2018