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Collections including paper arxiv:2106.09685

LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

Agents: An Open-source Framework for Autonomous Language Agents

Paper • 2309.07870 • Published Sep 14, 2023 • 42
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Paper • 2310.18940 • Published Oct 29, 2023
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Paper • 2504.01990 • Published Mar 31 • 301
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent

Paper • 2404.03648 • Published Apr 4, 2024 • 29

Parameter Efficient Fine-Tuning

This collection features fine-tuned models for tweet sentiment classification trained as part of LLM course.

neuralsrg/llm-course-hw3-dora

Text Generation • 0.3B • Updated Apr 11 • 2
neuralsrg/llm-course-hw3-lora

Text Generation • 0.3B • Updated Apr 11 • 2
neuralsrg/llm-course-hw3-tinyllama-qlora

Updated Apr 11
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

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 • 20
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

Research papers

LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings

Paper • 2504.15610 • Published Apr 22 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19 • 11
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models

Paper • 2403.08822 • Published Feb 28, 2024
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Paper • 2407.18242 • Published Jul 25, 2024

PEFT (Parameter Efficient Fine-Tuning)

PEFT (Parameter-Efficient Fine-Tuning): PEFT is a technique that focuses on updating only a small subset of the model’s parameters during fine-tuning.

thsluck/llm-course-hw3-lora

Text Generation • 0.3B • Updated Apr 11 • 3
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46
thsluck/llm-course-hw3-dora

Text Generation • 0.3B • Updated Apr 11 • 2
DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14, 2024 • 28

Video-Text-to-Text

Focusing on live streaming innovation

MoViNets: Mobile Video Networks for Efficient Video Recognition

Paper • 2103.11511 • Published Mar 21, 2021
Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Paper • 2506.08009 • Published Jun 9 • 27
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

impactful-papers

Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning

Paper • 2311.11077 • Published Nov 18, 2023 • 29
Tensor Product Attention Is All You Need

Paper • 2501.06425 • Published Jan 11 • 89
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Paper • 2403.03853 • Published Mar 6, 2024 • 66

LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings

Paper • 2504.15610 • Published Apr 22 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19 • 11
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models

Paper • 2403.08822 • Published Feb 28, 2024
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Paper • 2407.18242 • Published Jul 25, 2024

Agents: An Open-source Framework for Autonomous Language Agents

Paper • 2309.07870 • Published Sep 14, 2023 • 42
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Paper • 2310.18940 • Published Oct 29, 2023
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Paper • 2504.01990 • Published Mar 31 • 301
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent

Paper • 2404.03648 • Published Apr 4, 2024 • 29

PEFT (Parameter Efficient Fine-Tuning)

PEFT (Parameter-Efficient Fine-Tuning): PEFT is a technique that focuses on updating only a small subset of the model’s parameters during fine-tuning.

thsluck/llm-course-hw3-lora

Text Generation • 0.3B • Updated Apr 11 • 3
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46
thsluck/llm-course-hw3-dora

Text Generation • 0.3B • Updated Apr 11 • 2
DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14, 2024 • 28

Parameter Efficient Fine-Tuning

This collection features fine-tuned models for tweet sentiment classification trained as part of LLM course.

neuralsrg/llm-course-hw3-dora

Text Generation • 0.3B • Updated Apr 11 • 2
neuralsrg/llm-course-hw3-lora

Text Generation • 0.3B • Updated Apr 11 • 2
neuralsrg/llm-course-hw3-tinyllama-qlora

Updated Apr 11
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

Video-Text-to-Text

Focusing on live streaming innovation

MoViNets: Mobile Video Networks for Efficient Video Recognition

Paper • 2103.11511 • Published Mar 21, 2021
Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

Paper • 2506.08009 • Published Jun 9 • 27
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

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 • 20
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

impactful-papers

Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning

Paper • 2311.11077 • Published Nov 18, 2023 • 29
Tensor Product Attention Is All You Need

Paper • 2501.06425 • Published Jan 11 • 89
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Paper • 2403.03853 • Published Mar 6, 2024 • 66

Research papers

LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 46

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