nota-ai (Nota AI)

jykim310

updated a model 2 months ago

nota-ai/multilingual-e5-large-MGT-finetuned

Updated Jan 7

hancheolp

authored a paper 4 months ago

Assessing the Answerability of Queries in Retrieval-Augmented Code Generation

Paper • 2411.05547 • Published Nov 8, 2024

hancheolp

authored a paper 7 months ago

Self-Knowledge Distillation for Learning Ambiguity

Paper • 2406.09719 • Published Jun 14, 2024

thibcastells

authored a paper 11 months ago

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

Paper • 2402.02834 • Published Feb 5, 2024 • 16

ktho22

authored a paper 11 months ago

EdgeFusion: On-Device Text-to-Image Generation

Paper • 2404.11925 • Published Apr 18, 2024 • 22

skchoi

authored a paper 11 months ago

EdgeFusion: On-Device Text-to-Image Generation

Paper • 2404.11925 • Published Apr 18, 2024 • 22

tairenpiao

authored a paper 11 months ago

EdgeFusion: On-Device Text-to-Image Generation

Paper • 2404.11925 • Published Apr 18, 2024 • 22

thibcastells

authored a paper 11 months ago

EdgeFusion: On-Device Text-to-Image Generation

Paper • 2404.11925 • Published Apr 18, 2024 • 22

bokyeong1015

authored 2 papers 11 months ago

EdgeFusion: On-Device Text-to-Image Generation

Paper • 2404.11925 • Published Apr 18, 2024 • 22

LD-Pruner: Efficient Pruning of Latent Diffusion Models using Task-Agnostic Insights

Paper • 2404.11936 • Published Apr 18, 2024 • 1

geonmin-kim

authored a paper about 1 year ago

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

Paper • 2402.02834 • Published Feb 5, 2024 • 16

illian01

authored a paper about 1 year ago

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

Paper • 2402.02834 • Published Feb 5, 2024 • 16

bokyeong1015

authored a paper about 1 year ago

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

Paper • 2402.02834 • Published Feb 5, 2024 • 16

ktho22

authored 2 papers about 1 year ago

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

Paper • 2402.02834 • Published Feb 5, 2024 • 16

MobileSAMv2: Faster Segment Anything to Everything

Paper • 2312.09579 • Published Dec 15, 2023 • 24

thibcastells

authored a paper over 1 year ago

Automatic Neural Network Pruning that Efficiently Preserves the Model Accuracy

Paper • 2111.09635 • Published Nov 18, 2021 • 1

hancheolp

authored 2 papers over 1 year ago

A Unified Compression Framework for Efficient Speech-Driven Talking-Face Generation

Paper • 2304.00471 • Published Apr 2, 2023 • 1

Deep Model Compression Also Helps Models Capture Ambiguity

Paper • 2306.07061 • Published Jun 12, 2023

skchoi

authored a paper over 1 year ago

A Unified Compression Framework for Efficient Speech-Driven Talking-Face Generation

Paper • 2304.00471 • Published Apr 2, 2023 • 1

skchoi

authored a paper almost 2 years ago

On Architectural Compression of Text-to-Image Diffusion Models

Paper • 2305.15798 • Published May 25, 2023 • 4

Nota AI

AI & ML interests

nota-ai's activity

nota-ai/multilingual-e5-large-MGT-finetuned

Assessing the Answerability of Queries in Retrieval-Augmented Code Generation

Self-Knowledge Distillation for Learning Ambiguity

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

EdgeFusion: On-Device Text-to-Image Generation

EdgeFusion: On-Device Text-to-Image Generation

EdgeFusion: On-Device Text-to-Image Generation

EdgeFusion: On-Device Text-to-Image Generation

EdgeFusion: On-Device Text-to-Image Generation

LD-Pruner: Efficient Pruning of Latent Diffusion Models using Task-Agnostic Insights

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

MobileSAMv2: Faster Segment Anything to Everything

Automatic Neural Network Pruning that Efficiently Preserves the Model Accuracy

A Unified Compression Framework for Efficient Speech-Driven Talking-Face Generation

Deep Model Compression Also Helps Models Capture Ambiguity

A Unified Compression Framework for Efficient Speech-Driven Talking-Face Generation

On Architectural Compression of Text-to-Image Diffusion Models

AI & ML interests

Team members 41

nota-ai's activity