Measuring the Effects of Data Parallelism on Neural Network Training
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1811.03600
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Published
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2
Papers - Training Research
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Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
Paper • 1804.04235 • Published • 2 -
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Paper • 1905.11946 • Published • 2 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 57 -
Extending Context Window of Large Language Models via Positional Interpolation
Paper • 2306.15595 • Published • 52 -
ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
Paper • 2403.05135 • Published • 39 -
Algorithmic progress in language models
Paper • 2403.05812 • Published • 16 -
Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU
Paper • 2403.06504 • Published • 52 -
QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models
Paper • 2310.16795 • Published • 26 -
CoCa: Contrastive Captioners are Image-Text Foundation Models
Paper • 2205.01917 • Published • 2 -
Wide Residual Networks
Paper • 1605.07146 • Published • 2 -
Slimmable Encoders for Flexible Split DNNs in Bandwidth and Resource Constrained IoT Systems
Paper • 2306.12691 • Published • 2 -
Learning to Reason and Memorize with Self-Notes
Paper • 2305.00833 • Published • 4 -
Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance
Paper • 2310.10021 • Published • 2 -
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology
Paper • 2203.00585 • Published • 2 -
DeepNet: Scaling Transformers to 1,000 Layers
Paper • 2203.00555 • Published • 2 -
Gemma: Open Models Based on Gemini Research and Technology
Paper • 2403.08295 • Published • 41 -
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer
Paper • 2305.16380 • Published • 2 -
SELF: Language-Driven Self-Evolution for Large Language Model
Paper • 2310.00533 • Published • 2 -
GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length
Paper • 2310.00576 • Published • 2 -
JoMA: Demystifying Multilayer Transformers via JOint Dynamics of MLP and Attention
Paper • 2310.00535 • Published • 2 -
Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla
Paper • 2307.09458 • Published • 9 -
The Impact of Depth and Width on Transformer Language Model Generalization
Paper • 2310.19956 • Published • 8 -
A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity
Paper • 2305.13169 • Published • 2 -
MicroNAS: Memory and Latency Constrained Hardware-Aware Neural Architecture Search for Time Series Classification on Microcontrollers
Paper • 2310.18384 • Published • 2 -
PreNAS: Preferred One-Shot Learning Towards Efficient Neural Architecture Search
Paper • 2304.14636 • Published • 2 -
Can GPT-4 Perform Neural Architecture Search?
Paper • 2304.10970 • Published • 2 -
Neural Architecture Search: Insights from 1000 Papers
Paper • 2301.08727 • Published • 2 -
Unified Functional Hashing in Automatic Machine Learning
Paper • 2302.05433 • Published • 2 -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 102 -
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
Paper • 2310.06117 • Published • 3 -
Transformers Can Achieve Length Generalization But Not Robustly
Paper • 2402.09371 • Published • 12 -
Triple-Encoders: Representations That Fire Together, Wire Together
Paper • 2402.12332 • Published • 2 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 119 -
Veagle: Advancements in Multimodal Representation Learning
Paper • 2403.08773 • Published • 7 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 53 -
3D-VLA: A 3D Vision-Language-Action Generative World Model
Paper • 2403.09631 • Published • 6 -
StreamMultiDiffusion: Real-Time Interactive Generation with Region-Based Semantic Control
Paper • 2403.09055 • Published • 23 -
Vision Transformer with Quadrangle Attention
Paper • 2303.15105 • Published • 2 -
Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of Latent-Based Diffusion Models
Paper • 2312.11473 • Published • 2 -
Semi-Supervised Semantic Segmentation using Redesigned Self-Training for White Blood Cells
Paper • 2401.07278 • Published • 2 -
Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses
Paper • 2312.00763 • Published • 18 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 7 -
Unified Scaling Laws for Routed Language Models
Paper • 2202.01169 • Published • 2 -
Hash Layers For Large Sparse Models
Paper • 2106.04426 • Published • 2 -
Chain-of-Verification Reduces Hallucination in Large Language Models
Paper • 2309.11495 • Published • 37 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 68 -
Exploring Large Language Models' Cognitive Moral Development through Defining Issues Test
Paper • 2309.13356 • Published • 36 -
Large Language Models Cannot Self-Correct Reasoning Yet
Paper • 2310.01798 • Published • 30 -
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 36 -
TabLib: A Dataset of 627M Tables with Context
Paper • 2310.07875 • Published • 8 -
Rethinking Attention: Exploring Shallow Feed-Forward Neural Networks as an Alternative to Attention Layers in Transformers
Paper • 2311.10642 • Published • 23 -
Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise
Paper • 2212.11685 • Published • 2 -
Neural networks behave as hash encoders: An empirical study
Paper • 2101.05490 • Published • 2 -
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 71 -
Simple synthetic data reduces sycophancy in large language models
Paper • 2308.03958 • Published • 20 -
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining
Paper • 2305.10429 • Published • 2 -
Recurrent Drafter for Fast Speculative Decoding in Large Language Models
Paper • 2403.09919 • Published • 18 -
FouriScale: A Frequency Perspective on Training-Free High-Resolution Image Synthesis
Paper • 2403.12963 • Published • 6 -
Chart-based Reasoning: Transferring Capabilities from LLMs to VLMs
Paper • 2403.12596 • Published • 9 -
PERL: Parameter Efficient Reinforcement Learning from Human Feedback
Paper • 2403.10704 • Published • 54 -
End-to-End Object Detection with Transformers
Paper • 2005.12872 • Published • 2 -
RewardBench: Evaluating Reward Models for Language Modeling
Paper • 2403.13787 • Published • 18 -
VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis
Paper • 2403.13501 • Published • 9 -
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints
Paper • 2305.13245 • Published • 5 -
ReNoise: Real Image Inversion Through Iterative Noising
Paper • 2403.14602 • Published • 19 -
DreamReward: Text-to-3D Generation with Human Preference
Paper • 2403.14613 • Published • 33 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 2 -
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Paper • 2305.11738 • Published • 3 -
Shepherd: A Critic for Language Model Generation
Paper • 2308.04592 • Published • 27 -
DRLC: Reinforcement Learning with Dense Rewards from LLM Critic
Paper • 2401.07382 • Published • 2 -
DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging
Paper • 2402.02622 • Published • 3 -
TRIP: Temporal Residual Learning with Image Noise Prior for Image-to-Video Diffusion Models
Paper • 2403.17005 • Published • 13 -
SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions
Paper • 2403.16627 • Published • 20 -
LLM Agent Operating System
Paper • 2403.16971 • Published • 62 -
Prompt me a Dataset: An investigation of text-image prompting for historical image dataset creation using foundation models
Paper • 2309.01674 • Published • 2 -
Data Distributional Properties Drive Emergent In-Context Learning in Transformers
Paper • 2205.05055 • Published • 2 -
InternLM2 Technical Report
Paper • 2403.17297 • Published • 25 -
LIMA: Less Is More for Alignment
Paper • 2305.11206 • Published • 17 -
Masked Audio Generation using a Single Non-Autoregressive Transformer
Paper • 2401.04577 • Published • 37 -
Unsolvable Problem Detection: Evaluating Trustworthiness of Vision Language Models
Paper • 2403.20331 • Published • 14 -
DiJiang: Efficient Large Language Models through Compact Kernelization
Paper • 2403.19928 • Published • 9 -
Why Transformers Need Adam: A Hessian Perspective
Paper • 2402.16788 • Published • 1 -
Bigger is not Always Better: Scaling Properties of Latent Diffusion Models
Paper • 2404.01367 • Published • 18 -
Training LLMs over Neurally Compressed Text
Paper • 2404.03626 • Published • 20 -
Locating and Editing Factual Associations in GPT
Paper • 2202.05262 • Published • 1 -
Prompt-to-Prompt Image Editing with Cross Attention Control
Paper • 2208.01626 • Published • 1 -
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
Paper • 2107.07651 • Published • 1 -
Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation
Paper • 2404.06910 • Published • 1 -
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
Paper • 2404.07839 • Published • 36 -
Instruction Tuning with Human Curriculum
Paper • 2310.09518 • Published • 3 -
OOVs in the Spotlight: How to Inflect them?
Paper • 2404.08974 • Published • 1 -
All you need is a good init
Paper • 1511.06422 • Published • 1