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Collections including paper arxiv:2406.07496

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 • 26
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021 • 2
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 2

Training Large Language Models to Reason in a Continuous Latent Space

Paper • 2412.06769 • Published Dec 9, 2024 • 94
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Paper • 2408.03314 • Published Aug 6, 2024 • 63
ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights

Paper • 2406.14596 • Published Jun 20, 2024 • 5
A Comprehensive Survey of LLM Alignment Techniques: RLHF, RLAIF, PPO, DPO and More

Paper • 2407.16216 • Published Jul 23, 2024

TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31

Foundation AI Papers (II)

Iterative Reasoning Preference Optimization

Paper • 2404.19733 • Published Apr 30, 2024 • 50
Better & Faster Large Language Models via Multi-token Prediction

Paper • 2404.19737 • Published Apr 30, 2024 • 80
ORPO: Monolithic Preference Optimization without Reference Model

Paper • 2403.07691 • Published Mar 12, 2024 • 72
KAN: Kolmogorov-Arnold Networks

Paper • 2404.19756 • Published Apr 30, 2024 • 116

Evaluating Very Long-Term Conversational Memory of LLM Agents

Paper • 2402.17753 • Published Feb 27, 2024 • 19
StructLM: Towards Building Generalist Models for Structured Knowledge Grounding

Paper • 2402.16671 • Published Feb 26, 2024 • 27
Do Large Language Models Latently Perform Multi-Hop Reasoning?

Paper • 2402.16837 • Published Feb 26, 2024 • 29
Divide-or-Conquer? Which Part Should You Distill Your LLM?

Paper • 2402.15000 • Published Feb 22, 2024 • 23

TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31
Automatic Prompt Optimization with "Gradient Descent" and Beam Search

Paper • 2305.03495 • Published May 4, 2023 • 2

DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines

Paper • 2312.13382 • Published Dec 20, 2023 • 3
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Paper • 2310.03714 • Published Oct 5, 2023 • 37
TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31

TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3, 2024 • 50
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

Paper • 2404.12253 • Published Apr 18, 2024 • 55
SnapKV: LLM Knows What You are Looking for Before Generation

Paper • 2404.14469 • Published Apr 22, 2024 • 27
FlowMind: Automatic Workflow Generation with LLMs

Paper • 2404.13050 • Published Mar 17, 2024 • 34

Why do Learning Rates Transfer? Reconciling Optimization and Scaling Limits for Deep Learning

Paper • 2402.17457 • Published Feb 27, 2024
Curvature-Informed SGD via General Purpose Lie-Group Preconditioners

Paper • 2402.04553 • Published Feb 7, 2024
TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling

Paper • 2405.14578 • Published May 23, 2024 • 1

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 • 26
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021 • 2
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 2

TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31
Automatic Prompt Optimization with "Gradient Descent" and Beam Search

Paper • 2305.03495 • Published May 4, 2023 • 2

Training Large Language Models to Reason in a Continuous Latent Space

Paper • 2412.06769 • Published Dec 9, 2024 • 94
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Paper • 2408.03314 • Published Aug 6, 2024 • 63
ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights

Paper • 2406.14596 • Published Jun 20, 2024 • 5
A Comprehensive Survey of LLM Alignment Techniques: RLHF, RLAIF, PPO, DPO and More

Paper • 2407.16216 • Published Jul 23, 2024

DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines

Paper • 2312.13382 • Published Dec 20, 2023 • 3
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Paper • 2310.03714 • Published Oct 5, 2023 • 37
TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31

TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31

TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31

Foundation AI Papers (II)

Iterative Reasoning Preference Optimization

Paper • 2404.19733 • Published Apr 30, 2024 • 50
Better & Faster Large Language Models via Multi-token Prediction

Paper • 2404.19737 • Published Apr 30, 2024 • 80
ORPO: Monolithic Preference Optimization without Reference Model

Paper • 2403.07691 • Published Mar 12, 2024 • 72
KAN: Kolmogorov-Arnold Networks

Paper • 2404.19756 • Published Apr 30, 2024 • 116

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3, 2024 • 50
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

Paper • 2404.12253 • Published Apr 18, 2024 • 55
SnapKV: LLM Knows What You are Looking for Before Generation

Paper • 2404.14469 • Published Apr 22, 2024 • 27
FlowMind: Automatic Workflow Generation with LLMs

Paper • 2404.13050 • Published Mar 17, 2024 • 34

Evaluating Very Long-Term Conversational Memory of LLM Agents

Paper • 2402.17753 • Published Feb 27, 2024 • 19
StructLM: Towards Building Generalist Models for Structured Knowledge Grounding

Paper • 2402.16671 • Published Feb 26, 2024 • 27
Do Large Language Models Latently Perform Multi-Hop Reasoning?

Paper • 2402.16837 • Published Feb 26, 2024 • 29
Divide-or-Conquer? Which Part Should You Distill Your LLM?

Paper • 2402.15000 • Published Feb 22, 2024 • 23

Why do Learning Rates Transfer? Reconciling Optimization and Scaling Limits for Deep Learning

Paper • 2402.17457 • Published Feb 27, 2024
Curvature-Informed SGD via General Purpose Lie-Group Preconditioners

Paper • 2402.04553 • Published Feb 7, 2024
TextGrad: Automatic "Differentiation" via Text

Paper • 2406.07496 • Published Jun 11, 2024 • 31
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling

Paper • 2405.14578 • Published May 23, 2024 • 1

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