85 citations · 92 across the 29 of their papers we have counts for
14 papers · 1 filter
SOCIA-Nabla: Textual Gradient Meets Multi-Agent Orchestration for Automated Simulator Generation
Yuncheng Hua, Sion Weatherhead, Mehdi Jafari +2
In this paper, we present SOCIA-Nabla, an end-to-end, agentic framework that treats simulator construction asinstance optimization over code within a textual computation graph. Spe…
RELOOP: Recursive Retrieval with Multi-Hop Reasoner and Planners for Heterogeneous QA
Ruiyi Yang, Hao Xue, Imran Razzak +2
Retrieval-augmented generation (RAG) remains brittle on multi-step questions and heterogeneous evidence sources, trading accuracy against latency and token/tool budgets. This paper…
TradingGroup: A Multi-Agent Trading System with Self-Reflection and Data-Synthesis
Feng Tian, Flora D. Salim, Hao Xue
Recent advancements in large language models (LLMs) have enabled powerful agent-based applications in finance, particularly for sentiment analysis, financial report comprehension,…
CoughViT: A Self-Supervised Vision Transformer for Cough Audio Representation Learning
Justin Luong, Hao Xue, Flora D. Salim
Physicians routinely assess respiratory sounds during the diagnostic process, providing insight into the condition of a patient's airways. In recent years, AI-based diagnostic syst…
ZARA: Training-Free Motion Time-Series Reasoning via Evidence-Grounded LLM Agents
Zechen Li, Baiyu Chen, Hao Xue +1
Motion sensor time-series are central to Human Activity Recognition (HAR), yet conventional approaches are constrained to fixed activity sets and typically require costly parameter…
Bisecle: Binding and Separation in Continual Learning for Video Language Understanding
Yue Tan, Xiaoqian Hu, Hao Xue +2
Frontier vision-language models (VLMs) have made remarkable improvements in video understanding tasks. However, real-world videos typically exist as continuously evolving data stre…
Generate the Forest before the Trees -- A Hierarchical Diffusion model for Climate Downscaling
Declan J. Curran, Sanaa Hobeichi, Hira Saleem +2
Downscaling is essential for generating the high-resolution climate data needed for local planning, but traditional methods remain computationally demanding. Recent years have seen…
Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning
Ruiyi Yang, Hao Xue, Imran Razzak +3
Retrieval-Augmented Generation (RAG) systems empower large language models (LLMs) with external knowledge, yet struggle with efficiency-accuracy trade-offs when scaling to large kn…
SOCIA-: Textual Gradient Meets Multi-Agent Orchestration for Automated Simulator Generation
Yuncheng Hua, Sion Weatherhead, Mehdi Jafari +2
In this paper, we present SOCIA-, an end-to-end, agentic framework that treats simulator construction asinstance optimization over code within a textual computation graph.…
Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarks
Wilson Wongso, Hao Xue, Flora D. Salim
Understanding human mobility through Point-of-Interest (POI) trajectory modeling is increasingly important for applications such as urban planning, personalized services, and gener…
Evaluating the Bias in LLMs for Surveying Opinion and Decision Making in Healthcare
Yonchanok Khaokaew, Flora D. Salim, Andreas Züfle +5
Generative agents have been increasingly used to simulate human behaviour in silico, driven by large language models (LLMs). These simulacra serve as sandboxes for studying human b…
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…
Long Context Modeling with Ranked Memory-Augmented Retrieval
Ghadir Alselwi, Hao Xue, Shoaib Jameel +3
Effective long-term memory management is crucial for language models handling extended contexts. We introduce the Enhanced Ranked Memory Augmented Retrieval (ERMAR) framework, whic…
Beyond Single Pass, Looping Through Time: KG-IRAG with Iterative Knowledge Retrieval
Ruiyi Yang, Hao Xue, Imran Razzak +2
Graph Retrieval-Augmented Generation (GraphRAG) has proven highly effective in enhancing the performance of Large Language Models (LLMs) on tasks that require external knowledge. B…