Named entity recognition and relation extraction: State-of-the-art
With the advent of Web 2.0, there exist many online platforms that result in massive textual-
data production. With ever-increasing textual data at hand, it is of immense importance to …
data production. With ever-increasing textual data at hand, it is of immense importance to …
Data-driven materials research enabled by natural language processing and information extraction
Given the emergence of data science and machine learning throughout all aspects of
society, but particularly in the scientific domain, there is increased importance placed on …
society, but particularly in the scientific domain, there is increased importance placed on …
Toolformer: Language models can teach themselves to use tools
Abstract Language models (LMs) exhibit remarkable abilities to solve new tasks from just a
few examples or textual instructions, especially at scale. They also, paradoxically, struggle …
few examples or textual instructions, especially at scale. They also, paradoxically, struggle …
[图书][B] Pretrained transformers for text ranking: Bert and beyond
The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …
response to a query. Although the most common formulation of text ranking is search …
Exploiting cloze questions for few shot text classification and natural language inference
Some NLP tasks can be solved in a fully unsupervised fashion by providing a pretrained
language model with" task descriptions" in natural language (eg, Radford et al., 2019). While …
language model with" task descriptions" in natural language (eg, Radford et al., 2019). While …
How can we know what language models know?
Recent work has presented intriguing results examining the knowledge contained in
language models (LMs) by having the LM fill in the blanks of prompts such as “Obama is a …
language models (LMs) by having the LM fill in the blanks of prompts such as “Obama is a …
A comprehensive survey on automatic knowledge graph construction
Automatic knowledge graph construction aims at manufacturing structured human
knowledge. To this end, much effort has historically been spent extracting informative fact …
knowledge. To this end, much effort has historically been spent extracting informative fact …
Automatically identifying words that can serve as labels for few-shot text classification
A recent approach for few-shot text classification is to convert textual inputs to cloze
questions that contain some form of task description, process them with a pretrained …
questions that contain some form of task description, process them with a pretrained …
[图书][B] Machine learning for text: An introduction
CC Aggarwal, CC Aggarwal - 2018 - Springer
The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …
referred to as text mining, text analytics, or machine learning from text. The choice of …
Machine knowledge: Creation and curation of comprehensive knowledge bases
Equipping machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
relationships has been a longstanding goal of AI. Over the last decade, large-scale …