16 citations · 25 across the 14 of their papers we have counts for
13 papers · 1 filter
Unveiling the Generalization Power of Fine-Tuned Large Language Models
Haoran Yang, Yumeng Zhang, Jiaqi Xu +3
While Large Language Models (LLMs) have demonstrated exceptional multitasking abilities, fine-tuning these models on downstream, domain-specific datasets is often necessary to yiel…
Once Upon a in : Relative-Time Pretraining for Complex Temporal Reasoning
Sen Yang, Xin Li, Lidong Bing +1
Our physical world is constantly evolving over time, rendering challenges for pre-trained language models to understand and reason over the temporal contexts of texts. Existing wor…
Social Media Fashion Knowledge Extraction as Captioning
Yifei Yuan, Wenxuan Zhang, Yang Deng +1
Social media plays a significant role in boosting the fashion industry, where a massive amount of fashion-related posts are generated every day. In order to obtain the rich fashion…
EPA: Easy Prompt Augmentation on Large Language Models via Multiple Sources and Multiple Targets
Hongyuan Lu, Wai Lam
Large language models (LLMs) have shown promising performance on various NLP tasks via task prompting. And their performance can be further improved by appending task demonstration…
Enhancing Grammatical Error Correction Systems with Explanations
Yuejiao Fei, Leyang Cui, Sen Yang +3
Grammatical error correction systems improve written communication by detecting and correcting language mistakes. To help language learners better understand why the GEC system mak…
mPMR: A Multilingual Pre-trained Machine Reader at Scale
Weiwen Xu, Xin Li, Wai Lam +1
We present multilingual Pre-trained Machine Reader (mPMR), a novel method for multilingual machine reading comprehension (MRC)-style pre-training. mPMR aims to guide multilingual p…