General Knowledge
116 papers with code • 1 benchmarks • 2 datasets
This task aims to evaluate the ability of a model to answer general-knowledge questions.
Source: BIG-bench
Benchmarks
These leaderboards are used to track progress in General Knowledge
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Libraries
Use these libraries to find General Knowledge models and implementations
BIG-bench
BEAR-probe
Subtasks
Most implemented papers
Joey NMT: A Minimalist NMT Toolkit for Novices
joeynmt/joeynmt
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IJCNLP 2019
We present Joey NMT, a minimalist neural machine translation toolkit based on PyTorch that is specifically designed for novices.
ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
It is designed to represent the general knowledge involved in understanding language, improving natural language applications by allowing the application to better understand the meanings behind the words people use.
Automated Phrase Mining from Massive Text Corpora
As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality phrases from a text corpus.
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning
XiaoxinHe/TAPE
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With the advent of powerful large language models (LLMs) such as GPT or Llama2, which demonstrate an ability to reason and to utilize general knowledge, there is a growing need for techniques which combine the textual modelling abilities of LLMs with the structural learning capabilities of GNNs.
Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change Detection
KyanChen/TTP
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Change detection, a prominent research area in remote sensing, is pivotal in observing and analyzing surface transformations.
Learning to Understand Phrases by Embedding the Dictionary
Distributional models that learn rich semantic word representations are a success story of recent NLP research.
ConceptNet at SemEval-2017 Task 2: Extending Word Embeddings with Multilingual Relational Knowledge
This paper describes Luminoso's participation in SemEval 2017 Task 2, "Multilingual and Cross-lingual Semantic Word Similarity", with a system based on ConceptNet.
Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine Comprehension
intfloat/commonsense-rc
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SEMEVAL 2018
This paper describes our system for SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge.
Integrating Semantic Knowledge to Tackle Zero-shot Text Classification
JingqingZ/KG4ZeroShotText
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NAACL 2019
Insufficient or even unavailable training data of emerging classes is a big challenge of many classification tasks, including text classification.
