Summary of Breaking the Language Barrier: Can Direct Inference Outperform Pre-translation in Multilingual Llm Applications?, by Yotam Intrator et al.
Breaking the Language Barrier: Can Direct Inference Outperform Pre-Translation in Multilingual LLM Applications?
by Yotam Intrator, Matan Halfon, Roman Goldenberg, Reut Tsarfaty, Matan Eyal, Ehud Rivlin, Yossi Matias, Natalia Aizenberg
First submitted to arxiv on: 4 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This study investigates the effectiveness of direct inference without pre-translation in large language models like PaLM2 (Anil et al., 2023) for multilingual tasks. The authors comprehensively evaluate PaLM2 across 108 languages and 6 benchmarks, including open-end generative tasks. Their findings challenge the conventional practice of pre-translation, demonstrating that direct inference with PaLM2-L outperforms pre-translation in 94 out of 108 languages. This research has significant implications for multilingual applications, enabling more efficient and authentic linguistic processing. The study showcases the capabilities of PaLM2 models in multilingual settings, highlighting their potential to revolutionize tasks such as language translation, text summarization, and open-ended question answering. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trying to understand a conversation in a different language. Usually, we translate it into English first before understanding what’s being said. But this study shows that we might not need to do that anymore! The researchers looked at a special kind of AI model called PaLM2 and found that it can understand languages directly without needing translation. They tested it on 108 different languages and found that it worked really well in most cases, even better than translating first. This discovery could make it easier for people to communicate across language barriers, which is really important for things like international business, travel, or just understanding each other’s cultures. |
Keywords
* Artificial intelligence * Inference * Question answering * Summarization * Translation
