1 code implementation • 2 Feb 2024 • Weiting Tan, Yunmo Chen, Tongfei Chen, Guanghui Qin, Haoran Xu, Heidi C. Zhang, Benjamin Van Durme, Philipp Koehn
We introduce STAR (Stream Transduction with Anchor Representations), a novel Transformer-based model designed for efficient sequence-to-sequence transduction over streams.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 23 Jan 2024 • Lingfeng Shen, Weiting Tan, Sihao Chen, Yunmo Chen, Jingyu Zhang, Haoran Xu, Boyuan Zheng, Philipp Koehn, Daniel Khashabi
As the influence of large language models (LLMs) spans across global communities, their safety challenges in multilingual settings become paramount for alignment research.
1 code implementation • 16 Jan 2024 • Haoran Xu, Amr Sharaf, Yunmo Chen, Weiting Tan, Lingfeng Shen, Benjamin Van Durme, Kenton Murray, Young Jin Kim
However, even the top-performing 13B LLM-based translation models, like ALMA, does not match the performance of state-of-the-art conventional encoder-decoder translation models or larger-scale LLMs such as GPT-4.
no code implementations • 21 Dec 2023 • Weiting Tan, Chu-Cheng Lin, Jason Eisner
In this paper, we focus on the resulting challenge of imputing the latent alignment path that explains a given pair of input and output strings (e. g., during training).
no code implementations • 4 Nov 2023 • Weiting Tan, Haoran Xu, Lingfeng Shen, Shuyue Stella Li, Kenton Murray, Philipp Koehn, Benjamin Van Durme, Yunmo Chen
Large language models trained primarily in a monolingual setting have demonstrated their ability to generalize to machine translation using zero- and few-shot examples with in-context learning.
1 code implementation • 23 May 2023 • Haoran Xu, Weiting Tan, Shuyue Stella Li, Yunmo Chen, Benjamin Van Durme, Philipp Koehn, Kenton Murray
Incorporating language-specific (LS) modules is a proven method to boost performance in multilingual machine translation.
1 code implementation • 18 May 2023 • Lingfeng Shen, Weiting Tan, Boyuan Zheng, Daniel Khashabi
We provide theoretical foundations for this metric and its relationship with other prompt selection metrics, providing a comprehensive understanding of existing methods.
no code implementations • 10 Oct 2022 • Weiting Tan, Kevin Heffernan, Holger Schwenk, Philipp Koehn
Multilingual sentence representations from large models encode semantic information from two or more languages and can be used for different cross-lingual information retrieval and matching tasks.
1 code implementation • 23 Aug 2022 • Weiting Tan, Philipp Koehn
Mining high-quality bitexts for low-resource languages is challenging.
1 code implementation • AMTA 2022 • Weiting Tan, Shuoyang Ding, Huda Khayrallah, Philipp Koehn
Neural Machine Translation (NMT) models are known to suffer from noisy inputs.