DeepAI
Log In Sign Up

RuMedBench: A Russian Medical Language Understanding Benchmark

01/17/2022
by   Pavel Blinov, et al.
0

The paper describes the open Russian medical language understanding benchmark covering several task types (classification, question answering, natural language inference, named entity recognition) on a number of novel text sets. Given the sensitive nature of the data in healthcare, such a benchmark partially closes the problem of Russian medical dataset absence. We prepare the unified format labeling, data split, and evaluation metrics for new tasks. The remaining tasks are from existing datasets with a few modifications. A single-number metric expresses a model's ability to cope with the benchmark. Moreover, we implement several baseline models, from simple ones to neural networks with transformer architecture, and release the code. Expectedly, the more advanced models yield better performance, but even a simple model is enough for a decent result in some tasks. Furthermore, for all tasks, we provide a human evaluation. Interestingly the models outperform humans in the large-scale classification tasks. However, the advantage of natural intelligence remains in the tasks requiring more knowledge and reasoning.

READ FULL TEXT

page 1

page 2

page 3

page 4

05/01/2020

KLEJ: Comprehensive Benchmark for Polish Language Understanding

In recent years, a series of Transformer-based models unlocked major imp...
06/15/2021

CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark

Artificial Intelligence (AI), along with the recent progress in biomedic...
06/18/2021

GEM: A General Evaluation Benchmark for Multimodal Tasks

In this paper, we present GEM as a General Evaluation benchmark for Mult...
05/20/2021

KLUE: Korean Language Understanding Evaluation

We introduce Korean Language Understanding Evaluation (KLUE) benchmark. ...
10/29/2020

RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark

In this paper, we introduce an advanced Russian general language underst...
04/23/2018

Towards a Unified Natural Language Inference Framework to Evaluate Sentence Representations

We present a large scale unified natural language inference (NLI) datase...
06/20/2019

One-vs-All Models for Asynchronous Training: An Empirical Analysis

Any given classification problem can be modeled using multi-class or One...