Skip to content

Latest commit

 

History

History
102 lines (74 loc) · 9.94 KB

README.md

File metadata and controls

102 lines (74 loc) · 9.94 KB
Raw

Research

Just a list of papers i read everyday and notes to keep a track of them. I used to read a variety of papers pre 2023 and you can look at them in the Pre-2023 section.

2nd September 2023

Pre 2023

Papers

These will either be paper implementations or/and reviews of various papers and notes for conference sessions, I will read/watch over time. I currently research on Abstractive Summarization ( A task within NLP)

Adversarial Examples

  • Explaining and Harnessing Adversarial Examples [Paper] [Review]
  • Intriguing Properties of Neural Networks [Paper][Review]
  • Practical BlackBox attacks against machine learning [Paper][Review]
-->

Neural Style

Image Classification

  • Very Deep Convolutional Networks for Large Scale Image Recognition [Paper][Review]

One Shot Learning

  • Siamese Neural networks for One-Shot Image Recognition [Paper][Review]
  • Learning to compare: Relation Network for Few shot Learning [Paper][Review][Code]

Natural Language Processing

Sequence to Sequence Learning

  • Sequence to Sequence Learning with Neural Networks. [Paper][Review]

Attention Based Models

  • Neural Machine Translation by jointly learning to align and translate [Paper][Review]

Text Classification

  • Universal Language Model Fine-tuning for Text Classification [Paper][Review]

Machine Translation

  • Incorporating BERT for Machine Translation. [Paper][Review]

Abstractive Summarization

  • A Neural Attention Model for Abstractive Sentence Summarization [Paper][Review]
  • Abstractive Text Summarization Using Sequence to Sequence RNNs and Beyond [Paper][Review]
  • Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting [Paper][Review]
  • Improving Abstraction in Text Summarization [Paper][Review]
  • Multi-Reward Reinforced Summarization with Saliency and Entailment [Paper][Review]
  • Bottom-Up Abstractive Summarization [Paper][Review]
  • Topic Augmented Generator for Abstractive Summarization [Paper][Review]
  • Earlier Isn’t Always Better: Sub-aspect Analysis on Corpus and System Biases in Summarization [Paper][Review]
  • Neural Text Summarization: A Critical Evaluation [Paper][Review]
  • What have we achieved on Text Summarization [Paper][Review]
  • Re-evaluating evaluaton in Text Summarization [Paper][Review]
  • Asking and answering questions to evaluate the factual consistency of summaries [Paper][Review]
  • On Faithfulness and Factuality in Abstractive Summarization [Paper][Review]
  • FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization [Paper][Review]
  • Analyzing sentence fusion in Abstractive Summarization [Paper][Review]
  • On the Abstractiveness of Neural Document Summarization [Paper][Review]
  • Evaluating the Factual Consistency of Abstractive Text Summarization. [Paper][Review]
  • Summ-Eval: Re-evaluating Summarization Evaluation [Paper][Review]

Topic-Based & Query-Based Summarization

  • A Reinforced Topic-Aware Convolutional Sequence-to-Sequence Model for Abstractive Text Summarization [Paper][Review]
  • Query-Based Abstractive Summarization Using Neural Networks [Paper][Review]
  • Transforming Wikipedia into Augmented Data for Query Focused Summarization [Paper][Review]
  • Extreme Summarization with Topic Aware Convolutional Neural Networks [[Paper][v2][v1]][Review]

Language Modeling

  • CTRL: A Conditional Transformer Language Model for Controllable Generation [Paper][Review]

Training

  • Von Mises-Fisher Loss for training Seq2Seq Models with Continous Outputs [Paper][Review]
  • Neural Text Degeneration with Unlikelihood Training [Paper][Review]
  • The curious case of neural text degeneration [Paper] [Review]
  • Parameter Selection: Why We Should Pay More Attention to It [Paper] [Review]

Question Answering

  • Generalizing Question Answering System with Pre-trained Language Model Fine-tuning [Paper][Review]
  • MULTI QA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension [Paper][Review]

Word Representations and Embeddings

  • Deep Contextualized word representations - ELMO [Paper][Review]
  • Information-Theoretic Probing with Minimum Description Length [Paper][Review]
  • SimCSE: Simple constrastive learning for sentence embeddings [Paper] [Review]