World Knowledge
218 papers with code • 0 benchmarks • 1 datasets
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Libraries
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Most implemented papers
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Existing methods for gaining such steerability collect human labels of the relative quality of model generations and fine-tune the unsupervised LM to align with these preferences, often with reinforcement learning from human feedback (RLHF).
Measuring Massive Multitask Language Understanding
By comprehensively evaluating the breadth and depth of a model's academic and professional understanding, our test can be used to analyze models across many tasks and to identify important shortcomings.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
huggingface/transformers
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NeurIPS 2020
Large pre-trained language models have been shown to store factual knowledge in their parameters, and achieve state-of-the-art results when fine-tuned on downstream NLP tasks.
REALM: Retrieval-Augmented Language Model Pre-Training
Language model pre-training has been shown to capture a surprising amount of world knowledge, crucial for NLP tasks such as question answering.
Imagine This! Scripts to Compositions to Videos
ubc-vision/make-a-story
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ECCV 2018
Imagining a scene described in natural language with realistic layout and appearance of entities is the ultimate test of spatial, visual, and semantic world knowledge.
Mistral 7B
We introduce Mistral 7B v0. 1, a 7-billion-parameter language model engineered for superior performance and efficiency.
MEIM: Multi-partition Embedding Interaction Beyond Block Term Format for Efficient and Expressive Link Prediction
Knowledge graph embedding aims to predict the missing relations between entities in knowledge graphs.
CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
jonathanherzig/commonsenseqa
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NAACL 2019
To investigate question answering with prior knowledge, we present CommonsenseQA: a challenging new dataset for commonsense question answering.
Breaking NLI Systems with Sentences that Require Simple Lexical Inferences
We create a new NLI test set that shows the deficiency of state-of-the-art models in inferences that require lexical and world knowledge.
ASER: A Large-scale Eventuality Knowledge Graph
Understanding human's language requires complex world knowledge.
