Tianyu Liu

Table-to-Text Generation by Structure-Aware Seq2seq Learning

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Table-to-text generation aims to generate a description for a factual table which can be viewed as a set of field-value records. To encode both the content and the structure of a table, we propose a …

Incorporating Glosses into Neural Word Sense Disambiguation

2018

Word Sense Disambiguation (WSD) aims to identify the correct meaning of polysemous words in the particular context. Lexical resources like WordNet which are proved to be of great help for WSD in the knowledge-based methods. …

Analysis on the Application of Cryptographic Technology in the Communication Security of Intelligent Networked Vehicles

2021 · 2021 6th International Conference on Automation, Control and Robotics Engineering (CACRE)

Intelligent networked vehicles are rapidly developing in intelligence and networking. The communication architecture is becoming more complex, external interfaces are richer, and data types are more complex. Different from the information security of the traditional …

On the Core Elements of Volleyball Players' Special Physical Training

2021 · Applied & Educational Psychology

volleyball pays attention to mutual cooperation and confrontation. The whole game not only consumes a lot of physical energy, but also depends on the professional competitive level. The competitive level is affected by our own …

BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation

2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Yuchen Jiang, Tianyu Liu, Shuming Ma, Dongdong Zhang, Jian Yang, Haoyang Huang, Rico Sennrich, Ryan Cotterell, Mrinmaya Sachan, Ming Zhou. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational …

A Bilingual Parallel Corpus with Discourse Annotations

2022 · arXiv (Cornell University)

Machine translation (MT) has almost achieved human parity at sentence-level translation. In response, the MT community has, in part, shifted its focus to document-level translation. However, the development of document-level MT systems is hampered by …

RepCL: Exploring Effective Representation for Continual Text Classification

2023 · arXiv (Cornell University)

Continual learning (CL) aims to constantly learn new knowledge over time while avoiding catastrophic forgetting on old tasks. In this work, we focus on continual text classification under the class-incremental setting. Recent CL studies find …

Discourse Centric Evaluation of Machine Translation with a Densely Annotated Parallel Corpus

2023 · arXiv (Cornell University)

Several recent papers claim human parity at sentence-level Machine Translation (MT), especially in high-resource languages. Thus, in response, the MT community has, in part, shifted its focus to document-level translation. Translating documents requires a deeper …

Bi-Drop: Enhancing Fine-tuning Generalization via Synchronous sub-net Estimation and Optimization

2023 · arXiv (Cornell University)

Pretrained language models have achieved remarkable success in natural language understanding. However, fine-tuning pretrained models on limited training data tends to overfit and thus diminish performance. This paper presents Bi-Drop, a fine-tuning strategy that selectively …

Multiuser Resource Allocation for Semantic-Relay-Aided Text Transmissions

2023

Semantic communication (SemCom) is an emerging technology that extracts useful meaning from data and sends only relevant semantic information. Thus, it has the great potential to improve the spectrum efficiency of conventional wireless systems with …

PGDiffSeg: Prior-Guided Denoising Diffusion Model with Parameter-Shared Attention for Breast Cancer Segmentation

2024 · arXiv (Cornell University)

Early detection through imaging and accurate diagnosis is crucial in mitigating the high mortality rate associated with breast cancer. However, locating tumors from low-resolution and high-noise medical images is extremely challenging. Therefore, this paper proposes …