8 papers
AfriMTEB and AfriE5: Benchmarking and Adapting Text Embedding Models for African Languages
Kosei Uemura, Miaoran Zhang, David Ifeoluwa Adelani
Text embeddings are an essential building component of several NLP tasks such as retrieval-augmented generation which is crucial for preventing hallucinations in LLMs. Despite the…
AFRIDOC-MT: Document-level MT Corpus for African Languages
Jesujoba O. Alabi, Israel Abebe Azime, Miaoran Zhang +13
This paper introduces AFRIDOC-MT, a document-level multi-parallel translation dataset covering English and five African languages: Amharic, Hausa, Swahili, Yorùbá, and Zulu. The…
Unveiling the Key Factors for Distilling Chain-of-Thought Reasoning
Xinghao Chen, Zhijing Sun, Wenjin Guo +8
Large Language Models (LLMs) excel in reasoning tasks through Chain-of-Thought (CoT) prompting. However, CoT prompting greatly increases computational demands, which has prompted g…
Fine-Tuning Large Language Models to Translate: Will a Touch of Noisy Data in Misaligned Languages Suffice?
Dawei Zhu, Pinzhen Chen, Miaoran Zhang +3
Traditionally, success in multilingual machine translation can be attributed to three key factors in training data: large volume, diverse translation directions, and high quality.…
Human Speech Perception in Noise: Can Large Language Models Paraphrase to Improve It?
Anupama Chingacham, Miaoran Zhang, Vera Demberg +1
Large Language Models (LLMs) can generate text by transferring style attributes like formality resulting in formal or informal text. However, instructing LLMs to generate text that…
Exploring the Effectiveness and Consistency of Task Selection in Intermediate-Task Transfer Learning
Pin-Jie Lin, Miaoran Zhang, Marius Mosbach +1
Identifying beneficial tasks to transfer from is a critical step toward successful intermediate-task transfer learning. In this work, we experiment with 130 source-target task comb…