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07/10/2023
InPars Toolkit: A Unified and Reproducible Synthetic Data Generation Pipeline for Neural Information Retrieval
Recent work has explored Large Language Models (LLMs) to overcome the la...
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04/16/2023
Sabiá: Portuguese Large Language Models
As the capabilities of language models continue to advance, it is concei...
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01/04/2023
InPars-v2: Large Language Models as Efficient Dataset Generators for Information Retrieval
Recently, InPars introduced a method to efficiently use large language m...
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12/12/2022
In Defense of Cross-Encoders for Zero-Shot Retrieval
Bi-encoders and cross-encoders are widely used in many state-of-the-art ...
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09/22/2022
MonoByte: A Pool of Monolingual Byte-level Language Models
The zero-shot cross-lingual ability of models pretrained on multilingual...
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06/06/2022
No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval
Recent work has shown that small distilled language models are strong co...
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05/30/2022
Billions of Parameters Are Worth More Than In-domain Training Data: A case study in the Legal Case Entailment Task
Recent work has shown that language models scaled to billions of paramet...
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02/10/2022
