67 citations · 109 across the 45 of their papers we have counts for
38 papers · 1 filter
Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering
Li Zheng, Xin Zhang, Shuyi He +5
Accurate comprehension and controllable generation of emotion and rhetoric are pivotal for enhancing the reasoning capabilities of large language models (LLMs). Existing studies mo…
How Robust Are Large Language Models for Clinical Numeracy? An Empirical Study on Numerical Reasoning Abilities in Clinical Contexts
Minh-Vuong Nguyen, Fatemeh Shiri, Zhuang Li +1
Large Language Models (LLMs) are increasingly being explored for clinical question answering and decision support, yet safe deployment critically requires reliable handling of pati…
ARQUSUMM: Argument-aware Quantitative Summarization of Online Conversations
An Quang Tang, Xiuzhen Zhang, Minh Ngoc Dinh +1
Online conversations have become more prevalent on public discussion platforms (e.g. Reddit). With growing controversial topics, it is desirable to summarize not only diverse argum…
QQSUM: A Novel Task and Model of Quantitative Query-Focused Summarization for Review-based Product Question Answering
An Quang Tang, Xiuzhen Zhang, Minh Ngoc Dinh +1
Review-based Product Question Answering (PQA) allows e-commerce platforms to automatically address customer queries by leveraging insights from user reviews. However, existing PQA…
DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph Refinement
Shaoqing Lin, Chong Teng, Fei Li +3
Vision-Language Models (VLMs) generate discourse-level, multi-sentence visual descriptions, challenging text scene graph parsers built for single-sentence caption-to-graph mapping.…
TRIDENT: Enhancing Large Language Model Safety with Tri-Dimensional Diversified Red-Teaming Data Synthesis
Xiaorui Wu, Xiaofeng Mao, Fei Li +5
Large Language Models (LLMs) excel in various natural language processing tasks but remain vulnerable to generating harmful content or being exploited for malicious purposes. Altho…
LazyReview A Dataset for Uncovering Lazy Thinking in NLP Peer Reviews
Sukannya Purkayastha, Zhuang Li, Anne Lauscher +2
Peer review is a cornerstone of quality control in scientific publishing. With the increasing workload, the unintended use of `quick' heuristics, referred to as lazy thinking, has…
RIDE: Enhancing Large Language Model Alignment through Restyled In-Context Learning Demonstration Exemplars
Yuncheng Hua, Lizhen Qu, Zhuang Li +3
Alignment tuning is crucial for ensuring large language models (LLMs) behave ethically and helpfully. Current alignment approaches require high-quality annotations and significant…
Overview of the 2024 ALTA Shared Task: Detect Automatic AI-Generated Sentences for Human-AI Hybrid Articles
Diego Mollá, Qiongkai Xu, Zijie Zeng +1
The ALTA shared tasks have been running annually since 2010. In 2024, the purpose of the task is to detect machine-generated text in a hybrid setting where the text may contain por…
Scalable Frame-based Construction of Sociocultural NormBases for Socially-Aware Dialogues
Shilin Qu, Weiqing Wang, Xin Zhou +6
Sociocultural norms serve as guiding principles for personal conduct in social interactions, emphasizing respect, cooperation, and appropriate behavior, which is able to benefit ta…
On the Reliability of Large Language Models for Causal Discovery
Tao Feng, Lizhen Qu, Niket Tandon +3
This study investigates the efficacy of Large Language Models (LLMs) in causal discovery. Using newly available open-source LLMs, OLMo and BLOOM, which provide access to their pre-…
Automating IRAC Analysis in Malaysian Contract Law using a Semi-Structured Knowledge Base
Xiaoxi Kang, Lizhen Qu, Lay-Ki Soon +2
The effectiveness of Large Language Models (LLMs) in legal reasoning is often limited due to the unique legal terminologies and the necessity for highly specialized knowledge. Thes…
SCAR: Data Selection via Style Consistency-Aware Response Ranking for Efficient Instruction-Tuning of Large Language Models
Zhuang Li, Yuncheng Hua, Thuy-Trang Vu +3
Recent studies emphasize that manually ensuring a consistent response style and maintaining high data quality in training sets can significantly improve the performance of fine-tun…
NAP^2: A Benchmark for Naturalness and Privacy-Preserving Text Rewriting by Learning from Human
Shuo Huang, William MacLean, Xiaoxi Kang +5
The widespread use of cloud-based Large Language Models (LLMs) has heightened concerns over user privacy, as sensitive information may be inadvertently exposed during interactions…
IMO: Greedy Layer-Wise Sparse Representation Learning for Out-of-Distribution Text Classification with Pre-trained Models
Tao Feng, Lizhen Qu, Zhuang Li +3
Machine learning models have made incredible progress, but they still struggle when applied to examples from unseen domains. This study focuses on a specific problem of domain gene…
Detecting AI-Generated Sentences in Human-AI Collaborative Hybrid Texts: Challenges, Strategies, and Insights
Zijie Zeng, Shiqi Liu, Lele Sha +5
This study explores the challenge of sentence-level AI-generated text detection within human-AI collaborative hybrid texts. Existing studies of AI-generated text detection for hybr…
RENOVI: A Benchmark Towards Remediating Norm Violations in Socio-Cultural Conversations
Haolan Zhan, Zhuang Li, Xiaoxi Kang +14
Norm violations occur when individuals fail to conform to culturally accepted behaviors, which may lead to potential conflicts. Remediating norm violations requires social awarenes…
Improving Cross-Domain Low-Resource Text Generation through LLM Post-Editing: A Programmer-Interpreter Approach
Zhuang Li, Levon Haroutunian, Raj Tumuluri +2
Post-editing has proven effective in improving the quality of text generated by large language models (LLMs) such as GPT-3.5 or GPT-4, particularly when direct updating of their pa…
Let's Negotiate! A Survey of Negotiation Dialogue Systems
Haolan Zhan, Yufei Wang, Tao Feng +7
Negotiation is a crucial ability in human communication. Recently, there has been a resurgent research interest in negotiation dialogue systems, whose goal is to create intelligent…
SADAS: A Dialogue Assistant System Towards Remediating Norm Violations in Bilingual Socio-Cultural Conversations
Yuncheng Hua, Zhuang Li, Linhao Luo +8
In today's globalized world, bridging the cultural divide is more critical than ever for forging meaningful connections. The Socially-Aware Dialogue Assistant System (SADAS) is our…
Natural Language Processing for Dialects of a Language: A Survey
Aditya Joshi, Raj Dabre, Diptesh Kanojia +4
State-of-the-art natural language processing (NLP) models are trained on massive training corpora, and report a superlative performance on evaluation datasets. This survey delves i…
Compositional Generalization for Multi-label Text Classification: A Data-Augmentation Approach
Yuyang Chai, Zhuang Li, Jiahui Liu +4
Despite significant advancements in multi-label text classification, the ability of existing models to generalize to novel and seldom-encountered complex concepts, which are compos…
TMID: A Comprehensive Real-world Dataset for Trademark Infringement Detection in E-Commerce
Tongxin Hu, Zhuang Li, Xin Jin +2
Annually, e-commerce platforms incur substantial financial losses due to trademark infringements, making it crucial to identify and mitigate potential legal risks tied to merchant…
Reranking for Natural Language Generation from Logical Forms: A Study based on Large Language Models
Levon Haroutunian, Zhuang Li, Lucian Galescu +3
Large language models (LLMs) have demonstrated impressive capabilities in natural language generation. However, their output quality can be inconsistent, posing challenges for gene…