The increasing reliance on Large Language Models (LLMs) across academia and industry
necessitates a comprehensive understanding of their robustness to prompts. In response to …

This paper embarks on an exploration into the Large Language Model (LLM) datasets,
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …

Language models have become a key step to achieve state-of-the art results in many
different Natural Language Processing (NLP) tasks. Leveraging the huge amount of …

The evaluation of large language models (LLMs) is crucial to assess their performance and
mitigate potential security risks. In this paper, we introduce PromptBench, a unified library to …

In recent years, computer language area has witnessed important evolvement with
applications in different domains. Machine Translation MT technology, considered as a …

We present Unicoder, a universal language encoder that is insensitive to different
languages. Given an arbitrary NLP task, a model can be trained with Unicoder using training …

This paper describes the creation process and statistics of the official United Nations Parallel
Corpus, the first parallel corpus composed from United Nations documents published by the …

In this paper, we present Farasa, a fast and accurate Arabic segmenter. Our approach is
based on SVM-rank using linear kernels. We measure the performance of the segmenter in …

Abstract Word Sense Disambiguation is a longstanding task in Natural Language
Processing, lying at the core of human language understanding. However, the evaluation of …

We frame the task of machine translation evaluation as one of scoring machine translation
output with a sequence-to-sequence paraphraser, conditioned on a human reference. We …