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Found 8 papers, 4 papers with code
Multilingual Text Summarization on Financial Documents
The language models were fine-tuned on a financial document collection of three languages (English, Spanish, and Greek) and aim to identify the beginning of the summary narrative part of the document.
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal value of generative AI tools in many communities.
How Do Multilingual Models Remember? Investigating Multilingual Factual Recall Mechanisms
Large Language Models (LLMs) store and retrieve vast amounts of factual knowledge acquired during pre-training.
Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants
We investigate the potential scale of this vulnerability by measuring the degree to which AI assistants can complete assessment questions in standard university-level STEM courses.
Breaking the Language Barrier: Improving Cross-Lingual Reasoning with Structured Self-Attention
We evaluate the cross-lingual reasoning abilities of MultiLMs in two schemes: (1) where the language of the context and the question remain the same in the new languages that are tested (i. e., the reasoning is still monolingual, but the model must transfer the learned reasoning ability across languages), and (2) where the language of the context and the question is different (which we term code-switched reasoning).
Discovering Knowledge-Critical Subnetworks in Pretrained Language Models
In this work, we investigate whether pretrained language models contain various knowledge-critical subnetworks: particular sparse computational subgraphs that can, if removed, precisely suppress specific knowledge the model has memorized.
Stop Pre-Training: Adapt Visual-Language Models to Unseen Languages
Our evaluation across three distinct tasks (image-text retrieval, visual entailment, and natural language visual reasoning) demonstrates that this approach outperforms the state-of-the-art multilingual vision-language models without requiring large parallel corpora.
Discovering Language-neutral Sub-networks in Multilingual Language Models
Multilingual pre-trained language models transfer remarkably well on cross-lingual downstream tasks.
