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.
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)
- Explaining and Harnessing Adversarial Examples [Paper] [Review]
- Intriguing Properties of Neural Networks [Paper][Review]
- Practical BlackBox attacks against machine learning [Paper][Review]
- Siamese Neural networks for One-Shot Image Recognition [Paper][Review]
- Learning to compare: Relation Network for Few shot Learning [Paper][Review][Code]
- 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]
- 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]
- 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]