6 citations · 24 across the 10 of their papers we have counts for
10 papers
Lexical Entrainment for Conversational Systems
Zhengxiang Shi, Procheta Sen, Aldo Lipani
Conversational agents have become ubiquitous in assisting with daily tasks, and are expected to possess human-like features. One such feature is lexical entrainment (LE), a phenome…
DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
Zhengxiang Shi, Aldo Lipani
Prompt tuning (PT), where a small amount of trainable soft (continuous) prompt vectors is affixed to the input of language models (LM), has shown promising results across various t…
Rethink the Effectiveness of Text Data Augmentation: An Empirical Analysis
Zhengxiang Shi, Aldo Lipani
In recent years, language models (LMs) have made remarkable progress in advancing the field of natural language processing (NLP). However, the impact of data augmentation (DA) tech…
Self Contrastive Learning for Session-based Recommendation
Zhengxiang Shi, Xi Wang, Aldo Lipani
Session-based recommendation, which aims to predict the next item of users' interest as per an existing sequence interaction of items, has attracted growing applications of Contras…
Rethinking Semi-supervised Learning with Language Models
Zhengxiang Shi, Francesco Tonolini, Nikolaos Aletras +3
Semi-supervised learning (SSL) is a popular setting aiming to effectively utilize unlabelled data to improve model performance in downstream natural language processing (NLP) tasks…
When and What to Ask Through World States and Text Instructions: IGLU NLP Challenge Solution
Zhengxiang Shi, Jerome Ramos, To Eun Kim +3
In collaborative tasks, effective communication is crucial for achieving joint goals. One such task is collaborative building where builders must communicate with each other to con…
Don't Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner
Zhengxiang Shi, Aldo Lipani
Language models (LMs) trained on vast quantities of unlabelled data have greatly advanced the field of natural language processing (NLP). In this study, we re-visit the widely acce…
Attention-based Ingredient Phrase Parser
Zhengxiang Shi, Pin Ni, Meihui Wang +2
As virtual personal assistants have now penetrated the consumer market, with products such as Siri and Alexa, the research community has produced several works on task-oriented dia…
Learning to Execute Actions or Ask Clarification Questions
Zhengxiang Shi, Yue Feng, Aldo Lipani
Collaborative tasks are ubiquitous activities where a form of communication is required in order to reach a joint goal. Collaborative building is one of such tasks. We wish to deve…
StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts
Zhengxiang Shi, Qiang Zhang, Aldo Lipani
Inferring spatial relations in natural language is a crucial ability an intelligent system should possess. The bAbI dataset tries to capture tasks relevant to this domain (task 17…