5 citations · 9 across the 6 of their papers we have counts for
6 papers
Building Task Bots with Self-learning for Enhanced Adaptability, Extensibility, and Factuality
Xiaoying Zhang
Developing adaptable, extensible, and accurate task bots with minimal or zero human intervention is a significant challenge in dialog research. This thesis examines the obstacles a…
Self-Tuning: Instructing LLMs to Effectively Acquire New Knowledge through Self-Teaching
Xiaoying Zhang, Baolin Peng, Ye Tian +4
Large language models (LLMs) often struggle to provide up-to-date information due to their one-time training and the constantly evolving nature of the world. To keep LLMs current,…
Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation
Xiaoying Zhang, Baolin Peng, Ye Tian +5
Despite showing increasingly human-like abilities, large language models (LLMs) often struggle with factual inaccuracies, i.e. "hallucinations", even when they hold relevant knowle…
Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories?
Jingyan Zhou, Minda Hu, Junan Li +4
Making moral judgments is an essential step toward developing ethical AI systems. Prevalent approaches are mostly implemented in a bottom-up manner, which uses a large set of annot…
SGP-TOD: Building Task Bots Effortlessly via Schema-Guided LLM Prompting
Xiaoying Zhang, Baolin Peng, Kun Li +2
Building end-to-end task bots and maintaining their integration with new functionalities using minimal human efforts is a long-standing challenge in dialog research. Recently large…
Toward Self-learning End-to-End Task-Oriented Dialog Systems
Xiaoying Zhang, Baolin Peng, Jianfeng Gao +1
End-to-end task bots are typically learned over a static and usually limited-size corpus. However, when deployed in dynamic, changing, and open environments to interact with users,…