Tag: review

• GPT-Fathom Benchmarking Large Language Models to Decipher the Evolutionary Path towards GPT-4 and Beyond (04 Nov 2023)
  

  This is my reading note for GPT-Fathom: Benchmarking Large Language Models to Decipher the Evolutionary Path towards GPT-4 and Beyond. This paper evaluates several LLMs and found 1) openAI’s GPT significantly outperformed all other competitors and Claude 2 is #2; 2) techniques like SFT and RLHF benefits smaller models most; 3) as the model evolves, some metric may slightly degrade.

• Battle of the Backbones A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks (29 Oct 2023)
  

  This is my reading note for Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks. This paper benchmarks different vision backbones and found that supervised ConvNext may show best performance. After it, supervised swin-transformer and clip based transformer is also very competitive. Different vision tasks shows highly correlated performance for different backbones.

• Small-scale proxies for large-scale Transformer training instabilities (09 Oct 2023)
  

  This is my reading note for Small-scale proxies for large-scale Transformer training instabilities. This paper discusses the method to improve model training stability related to hyper parameter.

• A Comprehensive Survey on Multimodal Recommender Systems Taxonomy, Evaluation, and Future Directions (08 Oct 2023)
  

  This is my reading note for A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions. This paper provides a review for multimodality recommendation system. However, it doesn’t cover the method based on transformer. It still provides a good review on the metric of recommendation system.

• Scaling Vision Transformers (23 Sep 2023)
  

  This is my reading note for Scaling Vision Transformers. This paper provides a detailed comparison and study of designing vision transformer.

• An Empirical Study of Training End-to-End Vision-and-Language Transformers (21 Sep 2023)
  

  This is my reading note for An Empirical Study of Training End-to-End Vision-and-Language Transformers. This paper provides a good review and comparison of multi modality (video and text) model’s design choice.

• SeamlessM4T-Massively Multilingual & Multimodal Machine Translation (05 Sep 2023)
  

  This is my reading note 2/2 on SeamlessM4T-Massively Multilingual & Multimodal Machine Translation. It is end to end multi language translation system supports multimodality (text and audio). This paper also provides a good review on machine translation. This note focus on data preparation part of the paper and please read SeamlessM4T-data for the other part.

• SeamlessM4T-Massively Multilingual & Multimodal Machine Translation (04 Sep 2023)
  

  This is my reading note 1/2 on SeamlessM4T-Massively Multilingual & Multimodal Machine Translation. It is end to end multi language translation system supports multimodality (text and audio). This paper also provides a good review on machine translation. This note focus on data preparation part of the paper and please read SeamlessM4T-model for the other part.

• Multimodal Learning with Transformers A Survey (02 Sep 2023)
  

  This is my reading note on Multimodal Learning with Transformers A Survey. This a paper provides a very nice overview of the transformer based multimodality learning techniques.

• Tool Learning with Foundation Models (26 Aug 2023)
  

  This is my read note on Tool Learning with Foundation Models This is a nice review paper on how to use LLM with external tool to perform different tasks.

• Knowledge Distillation A Survey (25 Aug 2023)
  

  This is my reading note on Knowledge Distillation: A Survey. As a representative type of model compression and acceleration, knowledge distillation effectively learns a small student model from a large teacher model (p. 1)

• Large-scale Multi-Modal Pre-trained Models A Comprehensive Survey (21 Jul 2023)
  

  This is my reading note for Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey. It provides an OK review for multimodality pre-trained models without diving too much into details.

• Vision-Language Intelligence Tasks, Representation Learning, and Large Models (20 Jul 2023)
  

  This is my reading note for Vision-Language Intelligence: Tasks, Representation Learning, and Large Models. It is yet another review paper for pre-trained vision-language model. Check my reading note for another review paper in Large-scale Multi-Modal Pre-trained Models A Comprehensive Survey

• Scaling Laws for Generative Mixed-Modal Language Models (22 Jun 2023)
  

  This is my reading note for Scaling Laws for Generative Mixed-Modal Language Models. This paper provides a study of scaling raw on dataset size and model size in multimodality settings.