Language models are multilingual chain-of-thought reasoners
We evaluate the reasoning abilities of large language models in multilingual settings. We
introduce the Multilingual Grade School Math (MGSM) benchmark, by manually translating …
introduce the Multilingual Grade School Math (MGSM) benchmark, by manually translating …
Efficient utilization of pre-trained models: A review of sentiment analysis via prompt learning
K Bu, Y Liu, X Ju - Knowledge-Based Systems, 2023 - Elsevier
Sentiment analysis is one of the traditional well-known tasks in Natural Language
Processing (NLP) research. In recent years, Pre-trained Models (PMs) have become one of …
Processing (NLP) research. In recent years, Pre-trained Models (PMs) have become one of …
Zero-shot rumor detection with propagation structure via prompt learning
The spread of rumors along with breaking events seriously hinders the truth in the era of
social media. Previous studies reveal that due to the lack of annotated resources, rumors …
social media. Previous studies reveal that due to the lack of annotated resources, rumors …
Bloom+ 1: Adding language support to bloom for zero-shot prompting
The BLOOM model is a large publicly available multilingual language model, but its
pretraining was limited to 46 languages. To extend the benefits of BLOOM to other …
pretraining was limited to 46 languages. To extend the benefits of BLOOM to other …
RadAdapt: Radiology report summarization via lightweight domain adaptation of large language models
We systematically investigate lightweight strategies to adapt large language models (LLMs)
for the task of radiology report summarization (RRS). Specifically, we focus on domain …
for the task of radiology report summarization (RRS). Specifically, we focus on domain …
[HTML][HTML] QAmeleon: Multilingual QA with Only 5 Examples
The availability of large, high-quality datasets has been a major driver of recent progress in
question answering (QA). Such annotated datasets, however, are difficult and costly to …
question answering (QA). Such annotated datasets, however, are difficult and costly to …
Overcoming catastrophic forgetting in zero-shot cross-lingual generation
In this paper, we explore the challenging problem of performing a generative task in a target
language when labeled data is only available in English, using summarization as a case …
language when labeled data is only available in English, using summarization as a case …
Few-shot learning with multilingual language models
Large-scale generative language models such as GPT-3 are competitive few-shot learners.
While these models are known to be able to jointly represent many different languages, their …
While these models are known to be able to jointly represent many different languages, their …
Enhancing cross-lingual natural language inference by prompt-learning from cross-lingual templates
K Qi, H Wan, J Du, H Chen - … of the 60th Annual Meeting of the …, 2022 - aclanthology.org
Cross-lingual natural language inference (XNLI) is a fundamental task in cross-lingual
natural language understanding. Recently this task is commonly addressed by pre-trained …
natural language understanding. Recently this task is commonly addressed by pre-trained …
Modular and parameter-efficient multimodal fusion with prompting
Recent research has made impressive progress in large-scale multimodal pre-training. In
the context of the rapid growth of model size, it is necessary to seek efficient and flexible …
the context of the rapid growth of model size, it is necessary to seek efficient and flexible …