Readers can choose to read all these highlights on our console, which allows users to filter out papers using keywords and find related papers, patents, etc. In addition, we identified a large number of papers that have published their code and data. Here is the NeurIPS 2021 Papers with Code/Data page. You may also like to explore our "Best Paper" Digest (NIPS), which lists the most influential NIPS papers in the last 30 years. The Conference on Neural Information Processing Systems (NIPS) is one of the top machine learning conferences in the world.

The Conference on Empirical Methods in Natural Language Processing (EMNLP) is one of the top natural language processing conferences in the world. In 2019, it is to be held in Hong Kong, China. There were 1,813 long paper submissions, of which 465 were accepted and 1,063 short paper submissions, of which 218 were accepted. A large number of these papers also published their code ( code download link). To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper.

Paper Digest is a new research tool that uses artificial intelligence to produce summaries of research papers. In this post David Beer tests out this tool on his own research and reflects on what the increasing penetration of AI into cognition and research tells us about the current state of academic research. When you arrive at Paper Digest you are welcomed with a stark message: 'Artificial Intelligence summarizes academic articles for you'. Conjuring a vision of automated thinking and a world in which technology does the heavy lifting for us. These types of messages are everywhere, folded into the projected promises of what AI might yet achieve.

LONDON – They come from very different worlds, yet have remarkably similar tales to tell. One hails from Takasaki, Gunma Prefecture, while the other was brought up in the shadows of the Merendon mountains in the Sula Valley of northwestern Honduras. Bonding over a "love of good coffee and jazz," Yasutomo Takano and Cristian Mejia have come a long way since they first met four years ago while studying bibliometrics at the Tokyo Institute of Technology. Back then they were both enthusiastic students with a love for robotics and the "internet of things." Now, they are using their combined skills to solve challenges in academia.