15 citations · 21 across the 8 of their papers we have counts for
5 papers · 1 filter
Detect, Explain, Escalate: Sustainable Dialogue Breakdown Management for LLM Agents
Abdellah Ghassel, Xianzhi Li, Xiaodan Zhu
Large Language Models (LLMs) have demonstrated substantial capabilities in conversational AI applications, yet their susceptibility to dialogue breakdowns poses significant challen…
Entropy-Gated Branching for Efficient Test-Time Reasoning
Xianzhi Li, Ethan Callanan, Abdellah Ghassel +1
Test-time compute methods can significantly improve the reasoning capabilities and problem-solving accuracy of large language models (LLMs). However, these approaches require subst…
ChatGPT as Data Augmentation for Compositional Generalization: A Case Study in Open Intent Detection
Yihao Fang, Xianzhi Li, Stephen W. Thomas +1
Open intent detection, a crucial aspect of natural language understanding, involves the identification of previously unseen intents in user-generated text. Despite the progress mad…
Are ChatGPT and GPT-4 General-Purpose Solvers for Financial Text Analytics? A Study on Several Typical Tasks
Xianzhi Li, Samuel Chan, Xiaodan Zhu +4
The most recent large language models(LLMs) such as ChatGPT and GPT-4 have shown exceptional capabilities of generalist models, achieving state-of-the-art performance on a wide ran…
Learning Better Intent Representations for Financial Open Intent Classification
Xianzhi Li, Will Aitken, Xiaodan Zhu +1
With the recent surge of NLP technologies in the financial domain, banks and other financial entities have adopted virtual agents (VA) to assist customers. A challenging problem fo…