CLIRLGJun 4, 2023

bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark

Berkeley
arXiv:2306.02349v2223 citationsh-index: 84
Originality Synthesis-oriented
AI Analysis

This provides a standardized evaluation framework for Bulgarian language models, addressing a gap for this specific language community.

The authors introduced bgGLUE, a Bulgarian language understanding benchmark covering nine NLU tasks, and conducted the first systematic evaluation of pre-trained language models for Bulgarian, showing strong performance on sequence labeling tasks but significant room for improvement in complex reasoning tasks.

We present bgGLUE(Bulgarian General Language Understanding Evaluation), a benchmark for evaluating language models on Natural Language Understanding (NLU) tasks in Bulgarian. Our benchmark includes NLU tasks targeting a variety of NLP problems (e.g., natural language inference, fact-checking, named entity recognition, sentiment analysis, question answering, etc.) and machine learning tasks (sequence labeling, document-level classification, and regression). We run the first systematic evaluation of pre-trained language models for Bulgarian, comparing and contrasting results across the nine tasks in the benchmark. The evaluation results show strong performance on sequence labeling tasks, but there is a lot of room for improvement for tasks that require more complex reasoning. We make bgGLUE publicly available together with the fine-tuning and the evaluation code, as well as a public leaderboard at https://bgglue.github.io/, and we hope that it will enable further advancements in developing NLU models for Bulgarian.

Code Implementations2 repos
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes