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Collections including paper arxiv:2312.06550

The Chosen One: Consistent Characters in Text-to-Image Diffusion Models

Paper • 2311.10093 • Published Nov 16, 2023 • 59
Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models

Paper • 2311.12092 • Published Nov 20, 2023 • 23
DREAM: Diffusion Rectification and Estimation-Adaptive Models

Paper • 2312.00210 • Published Nov 30, 2023 • 17
HiFi Tuner: High-Fidelity Subject-Driven Fine-Tuning for Diffusion Models

Paper • 2312.00079 • Published Nov 30, 2023 • 17

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Paper • 2211.05100 • Published Nov 9, 2022 • 34
CsFEVER and CTKFacts: Acquiring Czech data for fact verification

Paper • 2201.11115 • Published Jan 26, 2022
Training language models to follow instructions with human feedback

Paper • 2203.02155 • Published Mar 4, 2022 • 24
FinGPT: Large Generative Models for a Small Language

Paper • 2311.05640 • Published Nov 3, 2023 • 32

LLM architecture

The Impact of Depth and Width on Transformer Language Model Generalization

Paper • 2310.19956 • Published Oct 30, 2023 • 10
Retentive Network: A Successor to Transformer for Large Language Models

Paper • 2307.08621 • Published Jul 17, 2023 • 172
RWKV: Reinventing RNNs for the Transformer Era

Paper • 2305.13048 • Published May 22, 2023 • 20
Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 96

Dataset pruning/cleaning/dedup

AlpaGasus: Training A Better Alpaca with Fewer Data

Paper • 2307.08701 • Published Jul 17, 2023 • 23
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

Paper • 2303.03915 • Published Mar 7, 2023 • 7
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset

Paper • 2309.04662 • Published Sep 9, 2023 • 24
SlimPajama-DC: Understanding Data Combinations for LLM Training

Paper • 2309.10818 • Published Sep 19, 2023 • 11

Data augmentation

DualMix: Unleashing the Potential of Data Augmentation for Online Class-Incremental Learning

Paper • 2303.07864 • Published Mar 14, 2023 • 1
Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks

Paper • 2305.13547 • Published May 22, 2023 • 1
MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning

Paper • 2304.09402 • Published Apr 19, 2023 • 2
LM-CPPF: Paraphrasing-Guided Data Augmentation for Contrastive Prompt-Based Few-Shot Fine-Tuning

Paper • 2305.18169 • Published May 29, 2023 • 1

Interpretability

A technical note on bilinear layers for interpretability

Paper • 2305.03452 • Published May 5, 2023 • 1
Interpreting Transformer's Attention Dynamic Memory and Visualizing the Semantic Information Flow of GPT

Paper • 2305.13417 • Published May 22, 2023 • 1
Explainable AI for Pre-Trained Code Models: What Do They Learn? When They Do Not Work?

Paper • 2211.12821 • Published Nov 23, 2022 • 2
The Linear Representation Hypothesis and the Geometry of Large Language Models

Paper • 2311.03658 • Published Nov 7, 2023 • 1

💫 Glossary https://osanseviero.github.io/hackerllama/blog/posts/hitchhiker_guide/

Understanding LLMs: A Comprehensive Overview from Training to Inference

Paper • 2401.02038 • Published Jan 4, 2024 • 65
Learning To Teach Large Language Models Logical Reasoning

Paper • 2310.09158 • Published Oct 13, 2023 • 1
ChipNeMo: Domain-Adapted LLMs for Chip Design

Paper • 2311.00176 • Published Oct 31, 2023 • 9
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Paper • 2308.09583 • Published Aug 18, 2023 • 7

Creative Robot Tool Use with Large Language Models

Paper • 2310.13065 • Published Oct 19, 2023 • 9
CodeCoT and Beyond: Learning to Program and Test like a Developer

Paper • 2308.08784 • Published Aug 17, 2023 • 5
Lemur: Harmonizing Natural Language and Code for Language Agents

Paper • 2310.06830 • Published Oct 10, 2023 • 34
CodePlan: Repository-level Coding using LLMs and Planning

Paper • 2309.12499 • Published Sep 21, 2023 • 79

The Chosen One: Consistent Characters in Text-to-Image Diffusion Models

Paper • 2311.10093 • Published Nov 16, 2023 • 59
Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models

Paper • 2311.12092 • Published Nov 20, 2023 • 23
DREAM: Diffusion Rectification and Estimation-Adaptive Models

Paper • 2312.00210 • Published Nov 30, 2023 • 17
HiFi Tuner: High-Fidelity Subject-Driven Fine-Tuning for Diffusion Models

Paper • 2312.00079 • Published Nov 30, 2023 • 17

Data augmentation

DualMix: Unleashing the Potential of Data Augmentation for Online Class-Incremental Learning

Paper • 2303.07864 • Published Mar 14, 2023 • 1
Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks

Paper • 2305.13547 • Published May 22, 2023 • 1
MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning

Paper • 2304.09402 • Published Apr 19, 2023 • 2
LM-CPPF: Paraphrasing-Guided Data Augmentation for Contrastive Prompt-Based Few-Shot Fine-Tuning

Paper • 2305.18169 • Published May 29, 2023 • 1

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Paper • 2211.05100 • Published Nov 9, 2022 • 34
CsFEVER and CTKFacts: Acquiring Czech data for fact verification

Paper • 2201.11115 • Published Jan 26, 2022
Training language models to follow instructions with human feedback

Paper • 2203.02155 • Published Mar 4, 2022 • 24
FinGPT: Large Generative Models for a Small Language

Paper • 2311.05640 • Published Nov 3, 2023 • 32

Interpretability

A technical note on bilinear layers for interpretability

Paper • 2305.03452 • Published May 5, 2023 • 1
Interpreting Transformer's Attention Dynamic Memory and Visualizing the Semantic Information Flow of GPT

Paper • 2305.13417 • Published May 22, 2023 • 1
Explainable AI for Pre-Trained Code Models: What Do They Learn? When They Do Not Work?

Paper • 2211.12821 • Published Nov 23, 2022 • 2
The Linear Representation Hypothesis and the Geometry of Large Language Models

Paper • 2311.03658 • Published Nov 7, 2023 • 1

LLM architecture

The Impact of Depth and Width on Transformer Language Model Generalization

Paper • 2310.19956 • Published Oct 30, 2023 • 10
Retentive Network: A Successor to Transformer for Large Language Models

Paper • 2307.08621 • Published Jul 17, 2023 • 172
RWKV: Reinventing RNNs for the Transformer Era

Paper • 2305.13048 • Published May 22, 2023 • 20
Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 96

💫 Glossary https://osanseviero.github.io/hackerllama/blog/posts/hitchhiker_guide/

Understanding LLMs: A Comprehensive Overview from Training to Inference

Paper • 2401.02038 • Published Jan 4, 2024 • 65
Learning To Teach Large Language Models Logical Reasoning

Paper • 2310.09158 • Published Oct 13, 2023 • 1
ChipNeMo: Domain-Adapted LLMs for Chip Design

Paper • 2311.00176 • Published Oct 31, 2023 • 9
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Paper • 2308.09583 • Published Aug 18, 2023 • 7

Dataset pruning/cleaning/dedup

AlpaGasus: Training A Better Alpaca with Fewer Data

Paper • 2307.08701 • Published Jul 17, 2023 • 23
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

Paper • 2303.03915 • Published Mar 7, 2023 • 7
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset

Paper • 2309.04662 • Published Sep 9, 2023 • 24
SlimPajama-DC: Understanding Data Combinations for LLM Training

Paper • 2309.10818 • Published Sep 19, 2023 • 11

Creative Robot Tool Use with Large Language Models

Paper • 2310.13065 • Published Oct 19, 2023 • 9
CodeCoT and Beyond: Learning to Program and Test like a Developer

Paper • 2308.08784 • Published Aug 17, 2023 • 5
Lemur: Harmonizing Natural Language and Code for Language Agents

Paper • 2310.06830 • Published Oct 10, 2023 • 34
CodePlan: Repository-level Coding using LLMs and Planning

Paper • 2309.12499 • Published Sep 21, 2023 • 79

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