67 citations · 109 across the 45 of their papers we have counts for
50 papers
Anticipating Social Consequences with Distributional World Models
Viet-Thanh Pham, Thuy-Trang Vu, Zhuang Li +2
Social world models predict how interactions develop after an action, helping agents negotiate, cooperate and mediate. In these situations, one action can lead to several plausible…
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…
Evidence-based Distributional Alignment for Large Language Models
Viet-Thanh Pham, Lizhen Qu, Zhuang Li +1
Distributional alignment enables large language models (LLMs) to predict how a target population distributes its responses across answer options, rather than collapsing disagreemen…
AutoPP: Towards Automated Product Poster Generation and Optimization
Jiahao Fan, Yuxin Qin, Wei Feng +10
Product posters blend striking visuals with informative text to highlight the product and capture customer attention. However, crafting appealing posters and manually optimizing th…
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…
Hi-Reco: High-Fidelity Real-Time Conversational Digital Humans
Hongbin Huang, Junwei Li, Tianxin Xie +8
High-fidelity digital humans are increasingly used in interactive applications, yet achieving both visual realism and real-time responsiveness remains a major challenge. We present…
MUGSQA: Novel Multi-Uncertainty-Based Gaussian Splatting Quality Assessment Method, Dataset, and Benchmarks
Tianang Chen, Jian Jin, Shilv Cai +2
Gaussian Splatting (GS) has recently emerged as a promising technique for 3D object reconstruction, delivering high-quality rendering results with significantly improved reconstruc…
Landsat30-AU: A Vision-Language Dataset for Australian Landsat Imagery
Sai Ma, Zhuang Li, John A Taylor
Vision language models (VLMs) that enable natural language interaction with satellite imagery can democratize Earth observation by accelerating expert workflows, making data access…
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…
EVOREFUSE: Evolutionary Prompt Optimization for Evaluation and Mitigation of LLM Over-Refusal to Pseudo-Malicious Instructions
Xiaorui Wu, Fei Li, Xiaofeng Mao +6
Large language models (LLMs) frequently refuse to respond to pseudo-malicious instructions: semantically harmless input queries triggering unnecessary LLM refusals due to conservat…
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…
Evaluating and Predicting Distorted Human Body Parts for Generated Images
Lu Ma, Kaibo Cao, Hao Liang +6
Recent advancements in text-to-image (T2I) models enable high-quality image synthesis, yet generating anatomically accurate human figures remains challenging. AI-generated images f…
Text-Driven Video Style Transfer with State-Space Models: Extending StyleMamba for Temporal Coherence
Chao Li, Minsu Park, Cristina Rossi +1
StyleMamba has recently demonstrated efficient text-driven image style transfer by leveraging state-space models (SSMs) and masked directional losses. In this paper, we extend the…
BiMarker: Enhancing Text Watermark Detection for Large Language Models with Bipolar Watermarks
Zhuang Li, Qiuping Yi, Zongcheng Ji +4
The rapid growth of Large Language Models (LLMs) raises concerns about distinguishing AI-generated text from human content. Existing watermarking techniques, like \kgw, struggle wi…
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…