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Collections including paper arxiv:2203.15556

Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 98
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 23
RoBERTa: A Robustly Optimized BERT Pretraining Approach

Paper • 1907.11692 • Published Jul 26, 2019 • 9
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Paper • 1910.01108 • Published Oct 2, 2019 • 21

A collection of arXiv papers from Chip Huyen's AI Engineering organized by chapter and ordered by when each appears in the book.

Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning

Paper • 2211.04325 • Published Oct 26, 2022 • 1
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 23
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021 • 1
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 2

Scaling Laws for Neural Language Models

Paper • 2001.08361 • Published Jan 23, 2020 • 9
Scaling Laws for Autoregressive Generative Modeling

Paper • 2010.14701 • Published Oct 28, 2020 • 1
Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
A Survey on Data Selection for Language Models

Paper • 2402.16827 • Published Feb 26, 2024 • 4

SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

Paper • 2408.15545 • Published Aug 28, 2024 • 38
Controllable Text Generation for Large Language Models: A Survey

Paper • 2408.12599 • Published Aug 22, 2024 • 65
To Code, or Not To Code? Exploring Impact of Code in Pre-training

Paper • 2408.10914 • Published Aug 20, 2024 • 44
Automated Design of Agentic Systems

Paper • 2408.08435 • Published Aug 15, 2024 • 40

Papers - Chinchilla

Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
Byte Latent Transformer: Patches Scale Better Than Tokens

Paper • 2412.09871 • Published Dec 13, 2024 • 108

Scaling Literature

Collection of Scaling Law Papers

Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Paper • 2408.03314 • Published Aug 6, 2024 • 63
Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
Scaling Laws for Precision

Paper • 2411.04330 • Published Nov 7, 2024 • 8
Transcending Scaling Laws with 0.1% Extra Compute

Paper • 2210.11399 • Published Oct 20, 2022

Scaling Laws 📏

Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Paper • 2206.10789 • Published Jun 22, 2022 • 4
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws

Paper • 2401.00448 • Published Dec 31, 2023 • 30
Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
Scaling Laws for Neural Language Models

Paper • 2001.08361 • Published Jan 23, 2020 • 9

LLM Tech Report

Qwen2.5 Technical Report

Paper • 2412.15115 • Published Dec 19, 2024 • 376
Qwen2.5-Coder Technical Report

Paper • 2409.12186 • Published Sep 18, 2024 • 151
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Paper • 2409.12122 • Published Sep 18, 2024 • 4
Qwen2.5-VL Technical Report

Paper • 2502.13923 • Published Feb 19 • 211

Finished Reading

Self-Play Preference Optimization for Language Model Alignment

Paper • 2405.00675 • Published May 1, 2024 • 27
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Paper • 2205.14135 • Published May 27, 2022 • 15
Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 98
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Paper • 2307.08691 • Published Jul 17, 2023 • 9

Papers - Training

SELF: Language-Driven Self-Evolution for Large Language Model

Paper • 2310.00533 • Published Oct 1, 2023 • 2
GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length

Paper • 2310.00576 • Published Oct 1, 2023 • 2
A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity

Paper • 2305.13169 • Published May 22, 2023 • 3
Transformers Can Achieve Length Generalization But Not Robustly

Paper • 2402.09371 • Published Feb 14, 2024 • 15

Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 98
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 23
RoBERTa: A Robustly Optimized BERT Pretraining Approach

Paper • 1907.11692 • Published Jul 26, 2019 • 9
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Paper • 1910.01108 • Published Oct 2, 2019 • 21

Scaling Literature

Collection of Scaling Law Papers

Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Paper • 2408.03314 • Published Aug 6, 2024 • 63
Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
Scaling Laws for Precision

Paper • 2411.04330 • Published Nov 7, 2024 • 8
Transcending Scaling Laws with 0.1% Extra Compute

Paper • 2210.11399 • Published Oct 20, 2022

A collection of arXiv papers from Chip Huyen's AI Engineering organized by chapter and ordered by when each appears in the book.

Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning

Paper • 2211.04325 • Published Oct 26, 2022 • 1
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 23
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021 • 1
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 2

Scaling Laws 📏

Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Paper • 2206.10789 • Published Jun 22, 2022 • 4
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws

Paper • 2401.00448 • Published Dec 31, 2023 • 30
Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
Scaling Laws for Neural Language Models

Paper • 2001.08361 • Published Jan 23, 2020 • 9

Scaling Laws for Neural Language Models

Paper • 2001.08361 • Published Jan 23, 2020 • 9
Scaling Laws for Autoregressive Generative Modeling

Paper • 2010.14701 • Published Oct 28, 2020 • 1
Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
A Survey on Data Selection for Language Models

Paper • 2402.16827 • Published Feb 26, 2024 • 4

LLM Tech Report

Qwen2.5 Technical Report

Paper • 2412.15115 • Published Dec 19, 2024 • 376
Qwen2.5-Coder Technical Report

Paper • 2409.12186 • Published Sep 18, 2024 • 151
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Paper • 2409.12122 • Published Sep 18, 2024 • 4
Qwen2.5-VL Technical Report

Paper • 2502.13923 • Published Feb 19 • 211

SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

Paper • 2408.15545 • Published Aug 28, 2024 • 38
Controllable Text Generation for Large Language Models: A Survey

Paper • 2408.12599 • Published Aug 22, 2024 • 65
To Code, or Not To Code? Exploring Impact of Code in Pre-training

Paper • 2408.10914 • Published Aug 20, 2024 • 44
Automated Design of Agentic Systems

Paper • 2408.08435 • Published Aug 15, 2024 • 40

Finished Reading

Self-Play Preference Optimization for Language Model Alignment

Paper • 2405.00675 • Published May 1, 2024 • 27
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Paper • 2205.14135 • Published May 27, 2022 • 15
Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 98
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Paper • 2307.08691 • Published Jul 17, 2023 • 9

Papers - Chinchilla

Training Compute-Optimal Large Language Models

Paper • 2203.15556 • Published Mar 29, 2022 • 11
Byte Latent Transformer: Patches Scale Better Than Tokens

Paper • 2412.09871 • Published Dec 13, 2024 • 108

Papers - Training

SELF: Language-Driven Self-Evolution for Large Language Model

Paper • 2310.00533 • Published Oct 1, 2023 • 2
GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length

Paper • 2310.00576 • Published Oct 1, 2023 • 2
A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity

Paper • 2305.13169 • Published May 22, 2023 • 3
Transformers Can Achieve Length Generalization But Not Robustly

Paper • 2402.09371 • Published Feb 14, 2024 • 15

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