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NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
We review the EfficientQA competition from NeurIPS 2020. The competition...
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Multi-task Retrieval for Knowledge-Intensive Tasks
Retrieving relevant contexts from a large corpus is a crucial step for t...
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A Memory Efficient Baseline for Open Domain Question Answering
Recently, retrieval systems based on dense representations have led to i...
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Generating Fact Checking Briefs
Fact checking at scale is difficult – while the number of active fact ch...
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Autoregressive Entity Retrieval
Entities are at the center of how we represent and aggregate knowledge. ...
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KILT: a Benchmark for Knowledge Intensive Language Tasks
Challenging problems such as open-domain question answering, fact checki...
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Video Understanding as Machine Translation
With the advent of large-scale multimodal video datasets, especially seq...
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Concept Matching for Low-Resource Classification
We propose a model to tackle classification tasks in the presence of ver...
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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Large pre-trained language models have been shown to store factual knowl...
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How Context Affects Language Models' Factual Predictions
When pre-trained on large unsupervised textual corpora, language models ...
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Zero-shot Entity Linking with Dense Entity Retrieval
We consider the zero-shot entity-linking challenge where each entity is ...
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How Decoding Strategies Affect the Verifiability of Generated Text
Language models are of considerable importance. They are used for pretra...
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Language Models as Knowledge Bases?
Recent progress in pretraining language models on large textual corpora ...
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SAFE: Self-Attentive Function Embeddings for Binary Similarity
The binary similarity problem consists in determining if two functions a...
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Unsupervised Features Extraction for Binary Similarity Using Graph Embedding Neural Networks
In this paper we consider the binary similarity problem that consists in...
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