# Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions

arXiv: https://arxiv.org/abs/2006.12442 · HTML: https://mlsanity.com/paper/2006.12442/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Jun 2020.

## Built on by (most cited first, 30 of 34)

- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [Survey of Hallucination in Natural Language Generation](https://mlsanity.com/paper/2202.03629/) (2022)
- [BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage](https://mlsanity.com/paper/2208.03188/) (2022)
- [Human Evaluation of Conversations is an Open Problem: comparing the sensitivity of various methods for evaluating dialogue agents](https://mlsanity.com/paper/2201.04723/) (2022)
- [Multi-Party Chat: Conversational Agents in Group Settings with Humans and Models](https://mlsanity.com/paper/2304.13835/) (2023)
- [AART: AI-Assisted Red-Teaming with Diverse Data Generation for New LLM-powered Applications](https://mlsanity.com/paper/2311.08592/) (2023)
- [Neural Approaches to Conversational Information Retrieval](https://mlsanity.com/paper/2201.05176/) (2022)
- [SaFeRDialogues: Taking Feedback Gracefully after Conversational Safety Failures](https://mlsanity.com/paper/2110.07518/) (2021)
- [Rome was built in 1776: A Case Study on Factual Correctness in Knowledge-Grounded Response Generation](https://mlsanity.com/paper/2110.05456/) (2021)
- [Investigating Robustness of Dialog Models to Popular Figurative Language Constructs](https://mlsanity.com/paper/2110.00687/) (2021)
- [Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision](https://mlsanity.com/paper/2509.14234/) (2025)
- [Multimodal Conversational AI: A Survey of Datasets and Approaches](https://mlsanity.com/paper/2205.06907/) (2022)
- [History-Aware Hierarchical Transformer for Multi-session Open-domain Dialogue System](https://mlsanity.com/paper/2302.00907/) (2023)
- [BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets](https://mlsanity.com/paper/2210.12687/) (2022)
- [Learning from data in the mixed adversarial non-adversarial case: Finding the helpers and ignoring the trolls](https://mlsanity.com/paper/2208.03295/) (2022)
- [Improving Open Language Models by Learning from Organic Interactions](https://mlsanity.com/paper/2306.04707/) (2023)
- [Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models](https://mlsanity.com/paper/2506.13681/) (2025)
- [Studying Catastrophic Forgetting in Neural Ranking Models](https://mlsanity.com/paper/2101.06984/) (2021)
- [Bilateral Personalized Dialogue Generation with Contrastive Learning](https://mlsanity.com/paper/2106.07857/) (2021)
- [Deep Transfer Learning & Beyond: Transformer Language Models in Information Systems Research](https://mlsanity.com/paper/2110.08975/) (2021)
- [Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track](https://mlsanity.com/paper/2506.19882/) (2025)
- [When Crowd Meets Persona: Creating a Large-Scale Open-Domain Persona Dialogue Corpus](https://mlsanity.com/paper/2304.00350/) (2023)
- [Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent](https://mlsanity.com/paper/2207.12021/) (2022)
- [The Open-domain Paradox for Chatbots: Common Ground as the Basis for Human-like Dialogue](https://mlsanity.com/paper/2303.11708/) (2023)
- [Chitchat as Interference: Adding User Backstories to Task-Oriented Dialogues](https://mlsanity.com/paper/2402.15248/) (2024)
- [Teach Me What to Say and I Will Learn What to Pick: Unsupervised Knowledge Selection Through Response Generation with Pretrained Generative Models](https://mlsanity.com/paper/2110.02067/) (2021)
- [Controllable Factuality in Document-Grounded Dialog Systems Using a Noisy Channel Model](https://mlsanity.com/paper/2210.17418/) (2022)
- [Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks](https://mlsanity.com/paper/2502.18339/) (2025)
- [An Approach to Inference-Driven Dialogue Management within a Social Chatbot](https://mlsanity.com/paper/2111.00570/) (2021)
- [Prior Lessons of Incremental Dialogue and Robot Action Management for the Age of Language Models](https://mlsanity.com/paper/2501.00953/) (2025)

## Abstract (arXiv)

We present our view of what is necessary to build an engaging open-domain conversational agent: covering the qualities of such an agent, the pieces of the puzzle that have been built so far, and the gaping holes we have not filled yet. We present a biased view, focusing on work done by our own group, while citing related work in each area. In particular, we discuss in detail the properties of continual learning, providing engaging content, and being well-behaved -- and how to measure success in providing them. We end with a discussion of our experience and learnings, and our recommendations to the community.