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20202025
most citedZero-shot Relation Classification from Side Information

9 citations · 24 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.CL2025

Sci-LoRA: Mixture of Scientific LoRAs for Cross-Domain Lay Paraphrasing

Ming Cheng, Jiaying Gong, Hoda Eldardiry

Lay paraphrasing aims to make scientific information accessible to audiences without technical backgrounds. However, most existing studies focus on a single domain, such as biomedi…

cs.CL2024

VTechAGP: An Academic-to-General-Audience Text Paraphrase Dataset and Benchmark Models

Ming Cheng, Jiaying Gong, Chenhan Yuan +3

Existing text simplification or paraphrase datasets mainly focus on sentence-level text generation in a general domain. These datasets are typically developed without using domain…

cs.CL2024★ 1 cited

Few-Shot Relation Extraction with Hybrid Visual Evidence

Jiaying Gong, Hoda Eldardiry

The goal of few-shot relation extraction is to predict relations between name entities in a sentence when only a few labeled instances are available for training. Existing few-shot…

cs.CL2021★ 6 cited

Prompt-based Zero-shot Relation Extraction with Semantic Knowledge Augmentation

Jiaying Gong, Hoda Eldardiry

In relation triplet extraction (RTE), recognizing unseen relations for which there are no training instances is a challenging task. Efforts have been made to recognize unseen relat…

cs.CL2020★ 9 cited

Zero-shot Relation Classification from Side Information

Jiaying Gong, Hoda Eldardiry

We propose a zero-shot learning relation classification (ZSLRC) framework that improves on state-of-the-art by its ability to recognize novel relations that were not present in tra…