32 citations · 202 across the 82 of their papers we have counts for
12 papers · 1 filter
REL: Working out is all you need
Toby Simonds, Jey Han Lau, Chaithanya Bandi
Recent developments, particularly OpenAI's O1 model, have demonstrated the remarkable potential of Large Language Models (LLMs) for complex reasoning tasks. Through analysis of O1'…
WHoW: A Cross-domain Approach for Analysing Conversation Moderation
Ming-Bin Chen, Lea Frermann, Jey Han Lau
We propose WHoW, an evaluation framework for analyzing the facilitation strategies of moderators across different domains/scenarios by examining their motives (Why), dialogue acts…
MoDEM: Mixture of Domain Expert Models
Toby Simonds, Kemal Kurniawan, Jey Han Lau
We propose a novel approach to enhancing the performance and efficiency of large language models (LLMs) by combining domain prompt routing with domain-specialized models. We introd…
KALE: An Artwork Image Captioning System Augmented with Heterogeneous Graph
Yanbei Jiang, Krista A. Ehinger, Jey Han Lau
Exploring the narratives conveyed by fine-art paintings is a challenge in image captioning, where the goal is to generate descriptions that not only precisely represent the visual…
WET: Overcoming Paraphrasing Vulnerabilities in Embeddings-as-a-Service with Linear Transformation Watermarks
Anudeex Shetty, Qiongkai Xu, Jey Han Lau
Embeddings-as-a-Service (EaaS) is a service offered by large language model (LLM) developers to supply embeddings generated by LLMs. Previous research suggests that EaaS is prone t…
To Aggregate or Not to Aggregate. That is the Question: A Case Study on Annotation Subjectivity in Span Prediction
Kemal Kurniawan, Meladel Mistica, Timothy Baldwin +1
This paper explores the task of automatic prediction of text spans in a legal problem description that support a legal area label. We use a corpus of problem descriptions written b…
An Interpretable and Crosslingual Method for Evaluating Second-Language Dialogues
Rena Gao, Jingxuan Wu, Xuetong Wu +4
We analyse the cross-lingual transferability of a dialogue evaluation framework that assesses the relationships between micro-level linguistic features (e.g. backchannels) and macr…
Interaction Matters: An Evaluation Framework for Interactive Dialogue Assessment on English Second Language Conversations
Rena Gao, Carsten Roever, Jey Han Lau
We present an evaluation framework for interactive dialogue assessment in the context of English as a Second Language (ESL) speakers. Our framework collects dialogue-level interact…
Factual Dialogue Summarization via Learning from Large Language Models
Rongxin Zhu, Jey Han Lau, Jianzhong Qi
Factual consistency is an important quality in dialogue summarization. Large language model (LLM)-based automatic text summarization models generate more factually consistent summa…
Evaluating Evidence Attribution in Generated Fact Checking Explanations
Rui Xing, Timothy Baldwin, Jey Han Lau
Automated fact-checking systems often struggle with trustworthiness, as their generated explanations can include hallucinations. In this work, we explore evidence attribution for f…
CMA-R:Causal Mediation Analysis for Explaining Rumour Detection
Lin Tian, Xiuzhen Zhang, Jey Han Lau
We apply causal mediation analysis to explain the decision-making process of neural models for rumour detection on Twitter. Interventions at the input and network level reveal the…
A Sentiment Consolidation Framework for Meta-Review Generation
Miao Li, Jey Han Lau, Eduard Hovy
Modern natural language generation systems with Large Language Models (LLMs) exhibit the capability to generate a plausible summary of multiple documents; however, it is uncertain…