# Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access

arXiv: https://arxiv.org/abs/2006.03533 · HTML: https://mlsanity.com/paper/2006.03533/

## Key facts

- Cited by 58 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Jun 2020.

## Built on by (most cited first, 30 of 58)

- [Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback](https://mlsanity.com/paper/2302.12813/) (2023)
- [MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems](https://mlsanity.com/paper/2305.14536/) (2023)
- [GODEL: Large-Scale Pre-Training for Goal-Directed Dialog](https://mlsanity.com/paper/2206.11309/) (2022)
- [PLATO-XL: Exploring the Large-scale Pre-training of Dialogue Generation](https://mlsanity.com/paper/2109.09519/) (2021)
- [Efficient Retrieval Augmented Generation from Unstructured Knowledge for Task-Oriented Dialog](https://mlsanity.com/paper/2102.04643/) (2021)
- [Opportunities and Challenges in Neural Dialog Tutoring](https://mlsanity.com/paper/2301.09919/) (2023)
- ["How Robust r u?": Evaluating Task-Oriented Dialogue Systems on Spoken Conversations](https://mlsanity.com/paper/2109.13489/) (2021)
- [Elastic Weight Removal for Faithful and Abstractive Dialogue Generation](https://mlsanity.com/paper/2303.17574/) (2023)
- [Fusing task-oriented and open-domain dialogues in conversational agents](https://mlsanity.com/paper/2109.04137/) (2021)
- [Adaptive Retrieval-Augmented Generation for Conversational Systems](https://mlsanity.com/paper/2407.21712/) (2024)
- [End-to-End Learning of Flowchart Grounded Task-Oriented Dialogs](https://mlsanity.com/paper/2109.07263/) (2021)
- [Learning to Select External Knowledge with Multi-Scale Negative Sampling](https://mlsanity.com/paper/2102.02096/) (2021)
- [VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator](https://mlsanity.com/paper/2105.11589/) (2021)
- [SUQL: Conversational Search over Structured and Unstructured Data with Large Language Models](https://mlsanity.com/paper/2311.09818/) (2023)
- [Where to Go for the Holidays: Towards Mixed-Type Dialogs for Clarification of User Goals](https://mlsanity.com/paper/2204.07299/) (2022)
- [KETOD: Knowledge-Enriched Task-Oriented Dialogue](https://mlsanity.com/paper/2205.05589/) (2022)
- [TOD-DA: Towards Boosting the Robustness of Task-oriented Dialogue Modeling on Spoken Conversations](https://mlsanity.com/paper/2112.12441/) (2021)
- [Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access Track in DSTC9](https://mlsanity.com/paper/2101.09276/) (2021)
- [Towards Large-Scale Interpretable Knowledge Graph Reasoning for Dialogue Systems](https://mlsanity.com/paper/2203.10610/) (2022)
- [CGoDial: A Large-Scale Benchmark for Chinese Goal-oriented Dialog Evaluation](https://mlsanity.com/paper/2211.11617/) (2022)
- [textitDial BeInfo for Faithfulness: Improving Factuality of Information-Seeking Dialogue via Behavioural Fine-Tuning](https://mlsanity.com/paper/2311.09800/) (2023)
- [Can I Be of Further Assistance? Using Unstructured Knowledge Access to Improve Task-oriented Conversational Modeling](https://mlsanity.com/paper/2106.09174/) (2021)
- [UniGDD: A Unified Generative Framework for Goal-Oriented Document-Grounded Dialogue](https://mlsanity.com/paper/2204.07770/) (2022)
- [AARGH! End-to-end Retrieval-Generation for Task-Oriented Dialog](https://mlsanity.com/paper/2209.03632/) (2022)
- [Should We Fine-Tune or RAG? Evaluating Different Techniques to Adapt LLMs for Dialogue](https://mlsanity.com/paper/2406.06399/) (2024)
- [HyKnow: End-to-End Task-Oriented Dialog Modeling with Hybrid Knowledge Management](https://mlsanity.com/paper/2105.06041/) (2021)
- [A Challenge on Semi-Supervised and Reinforced Task-Oriented Dialog Systems](https://mlsanity.com/paper/2207.02657/) (2022)
- ["What do others think?": Task-Oriented Conversational Modeling with Subjective Knowledge](https://mlsanity.com/paper/2305.12091/) (2023)
- [Adapting Document-Grounded Dialog Systems to Spoken Conversations using Data Augmentation and a Noisy Channel Model](https://mlsanity.com/paper/2112.08844/) (2021)
- [OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experience](https://mlsanity.com/paper/2206.12449/) (2022)

## Abstract (arXiv)

Most prior work on task-oriented dialogue systems are restricted to a limited coverage of domain APIs, while users oftentimes have domain related requests that are not covered by the APIs. In this paper, we propose to expand coverage of task-oriented dialogue systems by incorporating external unstructured knowledge sources. We define three sub-tasks: knowledge-seeking turn detection, knowledge selection, and knowledge-grounded response generation, which can be modeled individually or jointly. We introduce an augmented version of MultiWOZ 2.1, which includes new out-of-API-coverage turns and responses grounded on external knowledge sources. We present baselines for each sub-task using both conventional and neural approaches. Our experimental results demonstrate the need for further research in this direction to enable more informative conversational systems.