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Collections including paper arxiv:2212.10560

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 • 21
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

Synthetic Data Generation

Textbooks Are All You Need

Paper • 2306.11644 • Published Jun 20, 2023 • 146
Textbooks Are All You Need II: phi-1.5 technical report

Paper • 2309.05463 • Published Sep 11, 2023 • 88
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Paper • 2305.07759 • Published May 12, 2023 • 36
Scaling Synthetic Data Creation with 1,000,000,000 Personas

Paper • 2406.20094 • Published Jun 28, 2024 • 105

Proximal Policy Optimization Algorithms

Paper • 1707.06347 • Published Jul 20, 2017 • 11
Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 63
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 152
Training language models to follow instructions with human feedback

Paper • 2203.02155 • Published Mar 4, 2022 • 22

Text Instruction Papers

Self-Instruct: Aligning Language Model with Self Generated Instructions

Paper • 2212.10560 • Published Dec 20, 2022 • 9
Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

Paper • 2312.16171 • Published Dec 26, 2023 • 37
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Paper • 2401.14196 • Published Jan 25, 2024 • 67
AlpaCare:Instruction-tuned Large Language Models for Medical Application

Paper • 2310.14558 • Published Oct 23, 2023 • 4

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 5
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 12
Evaluating the Robustness to Instructions of Large Language Models

Paper • 2308.14306 • Published Aug 28, 2023 • 1

INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language Models

Paper • 2306.04757 • Published Jun 7, 2023 • 6
Evaluating Instruction-Tuned Large Language Models on Code Comprehension and Generation

Paper • 2308.01240 • Published Aug 2, 2023 • 2
Can Large Language Models Understand Real-World Complex Instructions?

Paper • 2309.09150 • Published Sep 17, 2023 • 2
Evaluating the Instruction-Following Robustness of Large Language Models to Prompt Injection

Paper • 2308.10819 • Published Aug 17, 2023

ibm-research/AttaQ

Viewer • Updated Jan 26, 2024 • 1.4k • 756 • 20
snorkelai/snorkel-curated-instruction-tuning

Preview • Updated Mar 11, 2024 • 32 • 10
corbyrosset/researchy_questions

Viewer • Updated Feb 29, 2024 • 96.4k • 558 • 30
argilla/ultrafeedback-binarized-preferences

Viewer • Updated Nov 30, 2023 • 63.6k • 326 • 80

Large Language Model (LLM) and NLP related papers.

LoRA+: Efficient Low Rank Adaptation of Large Models

Paper • 2402.12354 • Published Feb 19, 2024 • 6
The FinBen: An Holistic Financial Benchmark for Large Language Models

Paper • 2402.12659 • Published Feb 20, 2024 • 23
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization

Paper • 2402.13249 • Published Feb 20, 2024 • 13
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10, 2024 • 70

about 12 hours ago

A Picture is Worth More Than 77 Text Tokens: Evaluating CLIP-Style Models on Dense Captions

Paper • 2312.08578 • Published Dec 14, 2023 • 20
ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative Tasks

Paper • 2312.08583 • Published Dec 14, 2023 • 12
Vision-Language Models as a Source of Rewards

Paper • 2312.09187 • Published Dec 14, 2023 • 14
StemGen: A music generation model that listens

Paper • 2312.08723 • Published Dec 14, 2023 • 49

Dataset generation

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 5
ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Paper • 2202.07922 • Published Feb 16, 2022 • 1
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models

Paper • 2310.13671 • Published Oct 20, 2023 • 19
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4

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 • 21
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

INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language Models

Paper • 2306.04757 • Published Jun 7, 2023 • 6
Evaluating Instruction-Tuned Large Language Models on Code Comprehension and Generation

Paper • 2308.01240 • Published Aug 2, 2023 • 2
Can Large Language Models Understand Real-World Complex Instructions?

Paper • 2309.09150 • Published Sep 17, 2023 • 2
Evaluating the Instruction-Following Robustness of Large Language Models to Prompt Injection

Paper • 2308.10819 • Published Aug 17, 2023

Synthetic Data Generation

Textbooks Are All You Need

Paper • 2306.11644 • Published Jun 20, 2023 • 146
Textbooks Are All You Need II: phi-1.5 technical report

Paper • 2309.05463 • Published Sep 11, 2023 • 88
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Paper • 2305.07759 • Published May 12, 2023 • 36
Scaling Synthetic Data Creation with 1,000,000,000 Personas

Paper • 2406.20094 • Published Jun 28, 2024 • 105

ibm-research/AttaQ

Viewer • Updated Jan 26, 2024 • 1.4k • 756 • 20
snorkelai/snorkel-curated-instruction-tuning

Preview • Updated Mar 11, 2024 • 32 • 10
corbyrosset/researchy_questions

Viewer • Updated Feb 29, 2024 • 96.4k • 558 • 30
argilla/ultrafeedback-binarized-preferences

Viewer • Updated Nov 30, 2023 • 63.6k • 326 • 80

Proximal Policy Optimization Algorithms

Paper • 1707.06347 • Published Jul 20, 2017 • 11
Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 63
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 152
Training language models to follow instructions with human feedback

Paper • 2203.02155 • Published Mar 4, 2022 • 22

Large Language Model (LLM) and NLP related papers.

LoRA+: Efficient Low Rank Adaptation of Large Models

Paper • 2402.12354 • Published Feb 19, 2024 • 6
The FinBen: An Holistic Financial Benchmark for Large Language Models

Paper • 2402.12659 • Published Feb 20, 2024 • 23
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization

Paper • 2402.13249 • Published Feb 20, 2024 • 13
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10, 2024 • 70

Text Instruction Papers

Self-Instruct: Aligning Language Model with Self Generated Instructions

Paper • 2212.10560 • Published Dec 20, 2022 • 9
Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

Paper • 2312.16171 • Published Dec 26, 2023 • 37
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Paper • 2401.14196 • Published Jan 25, 2024 • 67
AlpaCare:Instruction-tuned Large Language Models for Medical Application

Paper • 2310.14558 • Published Oct 23, 2023 • 4

about 12 hours ago

A Picture is Worth More Than 77 Text Tokens: Evaluating CLIP-Style Models on Dense Captions

Paper • 2312.08578 • Published Dec 14, 2023 • 20
ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative Tasks

Paper • 2312.08583 • Published Dec 14, 2023 • 12
Vision-Language Models as a Source of Rewards

Paper • 2312.09187 • Published Dec 14, 2023 • 14
StemGen: A music generation model that listens

Paper • 2312.08723 • Published Dec 14, 2023 • 49

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 5
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 12
Evaluating the Robustness to Instructions of Large Language Models

Paper • 2308.14306 • Published Aug 28, 2023 • 1

Dataset generation

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 5
ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Paper • 2202.07922 • Published Feb 16, 2022 • 1
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models

Paper • 2310.13671 • Published Oct 20, 2023 • 19
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4

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