# CASPR: A Commonsense Reasoning-based Conversational Socialbot

arXiv: https://arxiv.org/abs/2110.05387 · HTML: https://mlsanity.com/paper/2110.05387/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 37 references that are in the map.
- First posted on arXiv 11 Oct 2021.

## Builds on (most cited first, 13 of 13)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Constraint Answer Set Programming without Grounding](https://mlsanity.com/paper/1804.11162/) (2018)
- [Neural Generation Meets Real People: Towards Emotionally Engaging Mixed-Initiative Conversations](https://mlsanity.com/paper/2008.12348/) (2020)
- [Policy-Driven Neural Response Generation for Knowledge-Grounded Dialogue Systems](https://mlsanity.com/paper/2005.12529/) (2020)
- [A Physician Advisory System for Chronic Heart Failure Management Based on Knowledge Patterns](https://mlsanity.com/paper/1610.08115/) (2016)
- [Knowledge-driven Natural Language Understanding of English Text and its Applications](https://mlsanity.com/paper/2101.11707/) (2021)
- [Computing Stable Models of Normal Logic Programs Without Grounding](https://mlsanity.com/paper/1709.00501/) (2017)
- [SQuARE: Semantics-based Question Answering and Reasoning Engine](https://mlsanity.com/paper/2009.10239/) (2020)
- [Conversational AI : Open Domain Question Answering and Commonsense Reasoning](https://mlsanity.com/paper/1909.08258/) (2019)
- [DiscASP: A Graph-based ASP System for Finding Relevant Consistent Concepts with Applications to Conversational Socialbots](https://mlsanity.com/paper/2109.08297/) (2021)

## Built on by (most cited first, 6 of 6)

- [Reliable Natural Language Understanding with Large Language Models and Answer Set Programming](https://mlsanity.com/paper/2302.03780/) (2023)
- [Automated Interactive Domain-Specific Conversational Agents that Understand Human Dialogs](https://mlsanity.com/paper/2303.08941/) (2023)
- [Towards Dynamic Consistency Checking in Goal-directed Predicate Answer Set Programming](https://mlsanity.com/paper/2110.12053/) (2021)
- [Let's Get Personal: Personal Questions Improve SocialBot Performance in the Alexa Prize](https://mlsanity.com/paper/2303.04953/) (2023)
- [Reliable Conversational Agents under ASP Control that Understand Natural Language](https://mlsanity.com/paper/2502.09237/) (2025)
- [Reliable Collaborative Conversational Agent System Based on LLMs and Answer Set Programming](https://mlsanity.com/paper/2505.06438/) (2025)

## Abstract (arXiv)

We report on the design and development of the CASPR system, a socialbot designed to compete in the Amazon Alexa Socialbot Challenge 4. CASPR's distinguishing characteristic is that it will use automated commonsense reasoning to truly "understand" dialogs, allowing it to converse like a human. Three main requirements of a socialbot are that it should be able to "understand" users' utterances, possess a strategy for holding a conversation, and be able to learn new knowledge. We developed techniques such as conversational knowledge template (CKT) to approximate commonsense reasoning needed to hold a conversation on specific topics. We present the philosophy behind CASPR's design as well as details of its implementation. We also report on CASPR's performance as well as discuss lessons learned.