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
1 code implementation • 29 Jan 2024 • William Gantt, Shabnam Behzad, Hannah Youngeun An, Yunmo Chen, Aaron Steven White, Benjamin Van Durme, Mahsa Yarmohammadi
We introduce MultiMUC, the first multilingual parallel corpus for template filling, comprising translations of the classic MUC-4 template filling benchmark into five languages: Arabic, Chinese, Farsi, Korean, and Russian.
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 • 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 • 2 Nov 2023 • Liqiang Jing, Ruosen Li, Yunmo Chen, Mengzhao Jia, Xinya Du
We introduce FAITHSCORE (Faithfulness to Atomic Image Facts Score), a reference-free and fine-grained evaluation metric that measures the faithfulness of the generated free-form answers from large vision-language models (LVLMs).
1 code implementation • 20 Oct 2023 • Yunmo Chen, William Gantt, Tongfei Chen, Aaron Steven White, Benjamin Van Durme
We present a conceptual framework that unifies a variety of evaluation metrics for different structured prediction tasks (e. g. event and relation extraction, syntactic and semantic parsing).
1 code implementation • 1 Jun 2023 • Paul Soulos, Edward Hu, Kate McCurdy, Yunmo Chen, Roland Fernandez, Paul Smolensky, Jianfeng Gao
To facilitate the learning of these symbolic sequences, we introduce a differentiable tree interpreter that compiles high-level symbolic tree operations into subsymbolic matrix operations on tensors.
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.
no code implementations • 20 Dec 2022 • Kangda Wei, Dawn Lawrie, Benjamin Van Durme, Yunmo Chen, Orion Weller
Answering complex questions often requires multi-step reasoning in order to obtain the final answer.
1 code implementation • 19 Dec 2022 • William Gantt, Reno Kriz, Yunmo Chen, Siddharth Vashishtha, Aaron Steven White
As information extraction (IE) systems have grown more adept at processing whole documents, the classic task of template filling has seen renewed interest as benchmark for document-level IE.
no code implementations • 13 Oct 2022 • Weiwei Gu, Boyuan Zheng, Yunmo Chen, Tongfei Chen, Benjamin Van Durme
We present an empirical study on methods for span finding, the selection of consecutive tokens in text for some downstream tasks.
2 code implementations • 12 Oct 2022 • Yunmo Chen, William Gantt, Weiwei Gu, Tongfei Chen, Aaron Steven White, Benjamin Van Durme
We present a novel iterative extraction model, IterX, for extracting complex relations, or templates (i. e., N-tuples representing a mapping from named slots to spans of text) within a document.
no code implementations • 25 May 2022 • Nils Holzenberger, Yunmo Chen, Benjamin Van Durme
Information Extraction (IE) researchers are mapping tasks to Question Answering (QA) in order to leverage existing large QA resources, and thereby improve data efficiency.
2 code implementations • EMNLP 2021 • Mahsa Yarmohammadi, Shijie Wu, Marc Marone, Haoran Xu, Seth Ebner, Guanghui Qin, Yunmo Chen, Jialiang Guo, Craig Harman, Kenton Murray, Aaron Steven White, Mark Dredze, Benjamin Van Durme
Zero-shot cross-lingual information extraction (IE) describes the construction of an IE model for some target language, given existing annotations exclusively in some other language, typically English.
no code implementations • EACL 2021 • Patrick Xia, Guanghui Qin, Siddharth Vashishtha, Yunmo Chen, Tongfei Chen, Chandler May, Craig Harman, Kyle Rawlins, Aaron Steven White, Benjamin Van Durme
We present LOME, a system for performing multilingual information extraction.
no code implementations • 21 Dec 2020 • Yunmo Chen, Sixing Lu, Fan Yang, Xiaojiang Huang, Xing Fan, Chenlei Guo
Query rewriting (QR) systems are widely used to reduce the friction caused by errors in a spoken language understanding pipeline.
1 code implementation • 20 Nov 2020 • Yunmo Chen, Tongfei Chen, Benjamin Van Durme
We recognize the task of event argument linking in documents as similar to that of intent slot resolution in dialogue, providing a Transformer-based model that extends from a recently proposed solution to resolve references to slots.
1 code implementation • ACL 2020 • Tongfei Chen, Yunmo Chen, Benjamin Van Durme
We propose a novel method for hierarchical entity classification that embraces ontological structure at both training and during prediction.
no code implementations • EMNLP (spnlp) 2020 • Yunmo Chen, Tongfei Chen, Seth Ebner, Aaron Steven White, Benjamin Van Durme
We ask whether text understanding has progressed to where we may extract event information through incremental refinement of bleached statements derived from annotation manuals.