Papers with translation capabilities

2 papers
Action-Concentrated Embedding Framework: This Is Your Captain Sign-tokening (2024.lrec-main)

Copied to clipboard

Challenge: ACE is a new sign token embedding framework that tracks a signer’s actions based on human posture estimation and captures the token embeds using a short-time Fourier transform.
Approach: They propose a novel sign token embedding framework that tracks a signer’s actions based on human posture estimation and a dedicated notation system tailored for sign language.
Outcome: The proposed framework outperforms previous studies in translation performance against a disaster sign language dataset and improves by up to 5.79% for BLEU-4 and 5.46% for ROUGE-L metric.
Searching for Needles in a Haystack: On the Role of Incidental Bilingualism in PaLM’s Translation Capability (2023.acl-long)

Copied to clipboard

Challenge: Large multilingual language models exhibit impressive zero- or few-shot machine translation capabilities, despite never having been explicitly and intentionally exposed to translation data.
Approach: They propose a mixed-method approach to measure and understand incidental bilingualism at scale using the Pathways Language Model.
Outcome: The proposed model is exposed to over 30 million translation pairs across at least 44 languages.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations