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Found 11 papers, 10 papers with code
Unveiling the Key Factors for Distilling Chain-of-Thought Reasoning
Large Language Models (LLMs) excel in reasoning tasks through Chain-of-Thought (CoT) prompting.
AFRIDOC-MT: Document-level MT Corpus for African Languages
This paper introduces AFRIDOC-MT, a document-level multi-parallel translation dataset covering English and five African languages: Amharic, Hausa, Swahili, Yor\`ub\'a, and Zulu.
Human Speech Perception in Noise: Can Large Language Models Paraphrase to Improve It?
We conduct the first study to evaluate LLMs on a novel task of generating acoustically intelligible paraphrases for better human speech perception in noise.
Exploring the Effectiveness and Consistency of Task Selection in Intermediate-Task Transfer Learning
Identifying beneficial tasks to transfer from is a critical step toward successful intermediate-task transfer learning.
Fine-Tuning Large Language Models to Translate: Will a Touch of Noisy Data in Misaligned Languages Suffice?
Traditionally, success in multilingual machine translation can be attributed to three key factors in training data: large volume, diverse translation directions, and high quality.
AAdaM at SemEval-2024 Task 1: Augmentation and Adaptation for Multilingual Semantic Textual Relatedness
This paper presents our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages.
The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis
In-context learning is a popular inference strategy where large language models solve a task using only a few labeled demonstrations without needing any parameter updates.
A Lightweight Method to Generate Unanswerable Questions in English
If a question cannot be answered with the available information, robust systems for question answering (QA) should know _not_ to answer.
MCSE: Multimodal Contrastive Learning of Sentence Embeddings
Learning semantically meaningful sentence embeddings is an open problem in natural language processing.
Knowledge Base Index Compression via Dimensionality and Precision Reduction
Finally, we show that it is possible to combine PCA with using 1bit per dimension.
Preventing Author Profiling through Zero-Shot Multilingual Back-Translation
Documents as short as a single sentence may inadvertently reveal sensitive information about their authors, including e. g. their gender or ethnicity.
