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05/26/2023
People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts
Although pre-trained named entity recognition (NER) models are highly ac...
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05/24/2023
Calc-X: Enriching Arithmetical Chain-of-Thoughts Datasets by Interaction with Symbolic Systems
This report overviews our ongoing work in enriching chain-of-thoughts da...
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05/23/2023
Concept-aware Training Improves In-context Learning Ability of Language Models
Many recent language models (LMs) of Transformers family exhibit so-call...
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05/11/2023
Think Twice: Measuring the Efficiency of Eliminating Prediction Shortcuts of Question Answering Models
While the Large Language Models (LLMs) dominate a majority of language u...
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04/04/2023
Resources and Few-shot Learners for In-context Learning in Slavic Languages
Despite the rapid recent progress in creating accurate and compact in-co...
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12/03/2022
What is Not in the Context? Evaluation of Few-shot Learners with Informative Demonstrations
Large language models demonstrate an emergent ability to learn a new tas...
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11/29/2022
Soft Alignment Objectives for Robust Adaptation in Machine Translation
Domain adaptation allows generative language models to address specific ...
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06/16/2022
Methods for Estimating and Improving Robustness of Language Models
Despite their outstanding performance, large language models (LLMs) suff...
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03/08/2022
Adapt𝒪r: Objective-Centric Adaptation Framework for Language Models
Progress in natural language processing research is catalyzed by the pos...
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09/15/2021
Regressive Ensemble for Machine Translation Quality Evaluation
This work introduces a simple regressive ensemble for evaluating machine...
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06/01/2021
WebMIaS on Docker: Deploying Math-Aware Search in a Single Line of Code
Math informational retrieval (MIR) search engines are absent in the wide...
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04/19/2021
When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting
Since the seminal work of Mikolov et al. (2013a) and Bojanowski et al. (...
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02/04/2021
One Size Does Not Fit All: Finding the Optimal N-gram Sizes for FastText Models across Languages
Unsupervised word representation learning from large corpora is badly ne...
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03/10/2020