← Authors

Christopher Re

127 papers · 2011–2025 · 17 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (22) 🐝 Cross-Pollinator (9) πŸƒ Academic Marathon (14) 🌍 Conference Polyglot (17) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (4) 🏠 Conference Loyalist (46) πŸ† Grand Slam πŸ‘₯ Mega-Team (40) 🀝 Dynamic Duo (26) πŸ”¬ Deep Specialist (17) πŸ† Keyword Champion (3) πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (51) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ’Ž Century Club (127) ⚑ Prolific Year (13) πŸ”₯ Unstoppable (15) ❓ The Questioner (2)

Conferences

NIPS (46) ICML (29) ICLR (24) ACL (7) JMLR (4) AISTATS (3) NAACL (2) COLT (2) AAAI (2) ICCV (1) EMNLP (1) IJCAI (1) CVPR (1) MIDL (1) MLHC (1) UAI (1) WACV (1)

Top co-authors

Tri Dao (26) Albert Gu (18) Atri Rudra (17) Ce Zhang (16) Frederic Sala (13) Beidi Chen (12) Simran Arora (11) Michael Zhang (10) Michael Poli (10) Karan Goel (10)

Keywords

weak supervision (9) stochastic gradient descent (8) model compression (8) large language model (7) representation learning (6) attention mechanism (5) sequence model (5) transfer learning (5) language model (5) foundation model (5) data augmentation (5) contrastive learning (4) neural network (4) convex optimization (4) semi-supervised learning (4) generative model (4) model architecture (3) structure learning (3) distributed learning (3) markov chain monte carlo (3)

Papers

Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data ICLR 2025
Towards Learning High-Precision Least Squares Algorithms with Sequence Models ICLR 2025
Scaling Laws for Precision ICLR 2025
HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation CVPR 2025
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers JMLR 2025
KernelBench: Can LLMs Write Efficient GPU Kernels? ICML 2025
An Architecture Search Framework for Inference-Time Techniques ICML 2025
Restructuring Vector Quantization with the Rotation Trick ICLR 2025
Cost-efficient Collaboration between On-device and Cloud Language Models ICML 2025
ThunderKittens: Simple, Fast, and $\textit{Adorable}$ Kernels ICLR 2025
Aioli: A Unified Optimization Framework for Language Model Data Mixing ICLR 2025
LoLCATs: On Low-Rank Linearizing of Large Language Models ICLR 2025
Smoothie: Label Free Language Model Routing NIPS 2024
State-Free Inference of State-Space Models: The *Transfer Function* Approach ICML 2024
Prospector Heads: Generalized Feature Attribution for Large Models & Data ICML 2024
Simple linear attention language models balance the recall-throughput tradeoff ICML 2024
Collage Diffusion WACV 2024
Zoology: Measuring and Improving Recall in Efficient Language Models ICLR 2024
Context-Aware Meta-Learning ICLR 2024
The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry ICLR 2024
FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores ICLR 2024
Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT ICML 2024
Mechanistic Design and Scaling of Hybrid Architectures ICML 2024
WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management Tasks NIPS 2024
RedPajama: an Open Dataset for Training Large Language Models NIPS 2024
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time ICML 2023
How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections ICLR 2023
Simple Hardware-Efficient Long Convolutions for Sequence Modeling ICML 2023
Ask Me Anything: A simple strategy for prompting language models ICLR 2023
Hungry Hungry Hippos: Towards Language Modeling with State Space Models ICLR 2023
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks ICML 2023
HAPI Explorer: Comprehension, Discovery, and Explanation on History of ML APIs AAAI 2023
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification NIPS 2023
Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture NIPS 2023
TART: A plug-and-play Transformer module for task-agnostic reasoning NIPS 2023
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions NIPS 2023
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models NIPS 2023
Hyena Hierarchy: Towards Larger Convolutional Language Models ICML 2023
Fast Algorithms for a New Relaxation of Optimal Transport COLT 2023
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU ICML 2023
Effectively Modeling Time Series with Simple Discrete State Spaces ICLR 2023
Skill-it! A data-driven skills framework for understanding and training language models NIPS 2023
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution NIPS 2023
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models NIPS 2023
A case for reframing automated medical image classification as segmentation NIPS 2023
Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations ICML 2022
Machine Learning on Graphs: A Model and Comprehensive Taxonomy JMLR 2022
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning ICML 2022
Monarch: Expressive Structured Matrices for Efficient and Accurate Training ICML 2022
Shoring up the foundations: fusing model embeddings and weak supervision UAI 2022
S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces NIPS 2022
Transform Once: Efficient Operator Learning in Frequency Domain NIPS 2022
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness NIPS 2022
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees NIPS 2022
Self-Supervised Learning of Brain Dynamics from Broad Neuroimaging Data NIPS 2022
Contrastive Adapters for Foundation Model Group Robustness NIPS 2022
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions NIPS 2022
Decentralized Training of Foundation Models in Heterogeneous Environments NIPS 2022
On the Parameterization and Initialization of Diagonal State Space Models NIPS 2022
Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity MLHC 2022
Metadata Shaping: A Simple Approach for Knowledge-Enhanced Language Models ACL 2022
TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval ACL 2022
VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction MIDL 2022
Domino: Discovering Systematic Errors with Cross-Modal Embeddings ICLR 2022
Efficiently Modeling Long Sequences with Structured State Spaces ICLR 2022
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models ICLR 2022
It’s Raw! Audio Generation with State-Space Models ICML 2022
Cut out the annotator, keep the cutout: better segmentation with weak supervision ICLR 2021
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training ICLR 2021
HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections ICML 2021
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation AISTATS 2021
Scatterbrain: Unifying Sparse and Low-rank Attention NIPS 2021
Rethinking Neural Operations for Diverse Tasks NIPS 2021
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers NIPS 2021
Robustness Gym: Unifying the NLP Evaluation Landscape NAACL 2021
Goodwill Hunting: Analyzing and Repurposing Off-the-Shelf Named Entity Linking Systems NAACL 2021
Catformer: Designing Stable Transformers via Sensitivity Analysis ICML 2021
Mandoline: Model Evaluation under Distribution Shift ICML 2021
Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text EMNLP 2021
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation ICLR 2021
On the Generalization Effects of Linear Transformations in Data Augmentation ICML 2020
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods ICML 2020
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering NIPS 2020
Ivy: Instrumental Variable Synthesis for Causal Inference AISTATS 2020
Low-Dimensional Hyperbolic Knowledge Graph Embeddings ACL 2020
Contextual Embeddings: When Are They Worth It? ACL 2020
HiPPO: Recurrent Memory with Optimal Polynomial Projections NIPS 2020
Understanding and Improving Information Transfer in Multi-Task Learning ICLR 2020
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps ICLR 2020
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems NIPS 2020
Learning Mixed-Curvature Representations in Product Spaces ICLR 2019
Hyperbolic Graph Convolutional Neural Networks NIPS 2019
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices NIPS 2019
Multi-Resolution Weak Supervision for Sequential Data NIPS 2019
On the Downstream Performance of Compressed Word Embeddings NIPS 2019
Training Complex Models with Multi-Task Weak Supervision AAAI 2019
Low-Precision Random Fourier Features for Memory-constrained Kernel Approximation AISTATS 2019
Scene Graph Prediction With Limited Labels ICCV 2019
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations ICML 2019
A Kernel Theory of Modern Data Augmentation ICML 2019
Learning Dependency Structures for Weak Supervision Models ICML 2019
Learning Compressed Transforms with Low Displacement Rank NIPS 2018
Weighted SGD for $\ell_p$ Regression with Randomized Preconditioning JMLR 2018
Representation Tradeoffs for Hyperbolic Embeddings ICML 2018
Training Classifiers with Natural Language Explanations ACL 2018
Inferring Generative Model Structure with Static Analysis NIPS 2017
Gaussian Quadrature for Kernel Features NIPS 2017
Learning the Structure of Generative Models without Labeled Data ICML 2017
Learning to Compose Domain-Specific Transformations for Data Augmentation NIPS 2017
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling IJCAI 2017
Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much NIPS 2016
Data Programming: Creating Large Training Sets, Quickly NIPS 2016
Sub-sampled Newton Methods with Non-uniform Sampling NIPS 2016
Cyclades: Conflict-free Asynchronous Machine Learning NIPS 2016
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width NIPS 2015
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm JMLR 2015
Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems ICML 2015
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care NIPS 2015
Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms NIPS 2015
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm ICML 2014
Parallel Feature Selection Inspired by Group Testing NIPS 2014
Understanding Tables in Context Using Standard NLP Toolkits ACL 2013
An Approximate, Efficient LP Solver for LP Rounding NIPS 2013
Toward a Noncommutative Arithmetic-geometric Mean Inequality: Conjectures, Case-studies, and Consequences COLT 2012
Factoring nonnegative matrices with linear programs NIPS 2012
Big Data versus the Crowd: Looking for Relationships in All the Right Places ACL 2012
Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NIPS 2011