Kehai Chen

Instance Weighting for Neural Machine Translation Domain Adaptation

2017

Instance weighting has been widely applied to phrase-based machine translation domain adaptation. However, it is challenging to be applied to Neural Machine Translation (NMT) directly, because NMT is not a linear model.

When Large Language Models Meet Vector Databases: A Survey

2024 · arXiv (Cornell University)

This survey explores the synergistic potential of Large Language Models (LLMs) and Vector Databases (VecDBs), a burgeoning but rapidly evolving research area. With the proliferation of LLMs comes a host of challenges, including hallucinations, outdated …

Paying More Attention to Source Context: Mitigating Unfaithful Translations from Large Language Model

2024 · arXiv (Cornell University)

Large language models (LLMs) have showcased impressive multilingual machine translation ability. However, unlike encoder-decoder style models, decoder-only LLMs lack an explicit alignment between source and target contexts. Analyzing contribution scores during generation processes revealed that …

Syntax-Directed Attention for Neural Machine Translation

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Attention mechanism, including global attention and local attention, plays a key role in neural machine translation (NMT). Global attention attends to all source words for word prediction. In comparison, local attention selectively looks at fixed-window …