21 citations · 31 across the 7 of their papers we have counts for
7 papers
Reliable Collaborative Conversational Agent System Based on LLMs and Answer Set Programming
Yankai Zeng, Gopal Gupta
As the Large-Language-Model-driven (LLM-driven) Artificial Intelligence (AI) bots became popular, people realized their strong potential in Task-Oriented Dialogue (TOD). However, b…
Building Trustworthy AI by Addressing its 16+2 Desiderata with Goal-Directed Commonsense Reasoning
Alexis R. Tudor, Yankai Zeng, Huaduo Wang +2
Current advances in AI and its applicability have highlighted the need to ensure its trustworthiness for legal, ethical, and even commercial reasons. Sub-symbolic machine learning…
Reliable Conversational Agents under ASP Control that Understand Natural Language
Yankai Zeng
Efforts have been made to make machines converse like humans in the past few decades. The recent techniques of Large Language Models (LLMs) make it possible to have human-like conv…
A Reliable Common-Sense Reasoning Socialbot Built Using LLMs and Goal-Directed ASP
Yankai Zeng, Abhiramon Rajashekharan, Kinjal Basu +3
The development of large language models (LLMs), such as GPT, has enabled the construction of several socialbots, like ChatGPT, that are receiving a lot of attention for their abil…
Automated Interactive Domain-Specific Conversational Agents that Understand Human Dialogs
Yankai Zeng, Abhiramon Rajasekharan, Parth Padalkar +3
Achieving human-like communication with machines remains a classic, challenging topic in the field of Knowledge Representation and Reasoning and Natural Language Processing. These…
Reliable Natural Language Understanding with Large Language Models and Answer Set Programming
Abhiramon Rajasekharan, Yankai Zeng, Parth Padalkar +1
Humans understand language by extracting information (meaning) from sentences, combining it with existing commonsense knowledge, and then performing reasoning to draw conclusions.…
Weakly-Supervised Visual-Retriever-Reader for Knowledge-based Question Answering
Man Luo, Yankai Zeng, Pratyay Banerjee +1
Knowledge-based visual question answering (VQA) requires answering questions with external knowledge in addition to the content of images. One dataset that is mostly used in evalua…