mlsanityData to 7 Oct 2026

BORT: Back and Denoising Reconstruction for End-to-End Task-Oriented Dialog

arXiv 2205.02471 ↗First posted 5 May 2022cs.CLcited by 20

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Abstract (arXiv)

A typical end-to-end task-oriented dialog system transfers context into dialog state, and upon which generates a response, which usually faces the problem of error propagation from both previously generated inaccurate dialog states and responses, especially in low-resource scenarios. To alleviate these issues, we propose BORT, a back and denoising reconstruction approach for end-to-end task-oriented dialog system. Squarely, to improve the accuracy of dialog states, back reconstruction is used to reconstruct the original input context from the generated dialog states since inaccurate dialog states cannot recover the corresponding input context. To enhance the denoising capability of the model to reduce the impact of error propagation, denoising reconstruction is used to reconstruct the corrupted dialog state and response. Extensive experiments conducted on MultiWOZ 2.0 and CamRest676 show the effectiveness of BORT. Furthermore, BORT demonstrates its advanced capabilities in the zero-shot domain and low-resource scenarios.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 26 of its 41 references that are in the map. First posted on arXiv 5 May 2022.

Builds on

26 of 41 references.

References · 26

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  4. 2018Deep contextualized word representationscited by 2,285
  5. 2020Multilingual Denoising Pre-training for Neural Machine Translationcited by 1,028
  6. 2018MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modellingcited by 760
  7. 2020A Simple Language Model for Task-Oriented Dialoguecited by 331
  8. 2016A Network-based End-to-End Trainable Task-oriented Dialogue Systemcited by 252
  9. 2020TOD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialoguecited by 185
  10. 2017Unsupervised Neural Machine Translationcited by 148
  11. 2018Phrase-Based & Neural Unsupervised Machine Translationcited by 138
  12. 2020UBAR: Towards Fully End-to-End Task-Oriented Dialog Systems with GPT-2cited by 111
14 more
  1. 2019Hello, It's GPT-2 -- How Can I Help You? Towards the Use of Pretrained Language Models for Task-Oriented Dialogue Systemscited by 110
  2. 2020MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systemscited by 103
  3. 2019Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Contextcited by 99
  4. 2019SUMBT: Slot-Utterance Matching for Universal and Scalable Belief Trackingcited by 63
  5. 2019Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Modelscited by 53
  6. 2021Shades of BLEU, Flavours of Success: The Case of MultiWOZcited by 48
  7. 2020A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learningcited by 47
  8. 2019Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attentioncited by 43
  9. 2020LAVA: Latent Action Spaces via Variational Auto-encoding for Dialogue Policy Optimizationcited by 30
  10. 2016Neural Machine Translation with Reconstructioncited by 28
  11. 2020Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue Systemcited by 28
  12. 2019Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Modelscited by 25
  13. 2021Domain State Tracking for a Simplified Dialogue Systemcited by 17
  14. 2018Translating Pro-Drop Languages with Reconstruction Modelscited by 14

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 8; 2023: 7; 2024: 3; 2025: 1; 2026: 1.

20 papers.

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  1. 2023Task-Optimized Adapters for an End-to-End Task-Oriented Dialogue Systemcited by 30
  2. 2022ByGPT5: End-to-End Style-conditioned Poetry Generation with Token-free Language Modelscited by 25
  3. 2023End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directionscited by 17
  4. 2022Mars: Modeling Context & State Representations with Contrastive Learning for End-to-End Task-Oriented Dialogcited by 11
  5. 2022Q-TOD: A Query-driven Task-oriented Dialogue Systemcited by 10
  6. 2022KRLS: Improving End-to-End Response Generation in Task Oriented Dialog with Reinforced Keywords Learningcited by 9
  7. 2023DiactTOD: Learning Generalizable Latent Dialogue Acts for Controllable Task-Oriented Dialogue Systemscited by 6
  8. 2023InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue Systemscited by 5
  9. 2022DFM: Dialogue Foundation Model for Universal Large-Scale Dialogue-Oriented Task Learningcited by 3
  10. 2022MoNET: Tackle State Momentum via Noise-Enhanced Training for Dialogue State Trackingcited by 3
  11. 2023Zero-Shot Generalizable End-to-End Task-Oriented Dialog System using Context Summarization and Domain Schemacited by 3
  12. 2022UBARv2: Towards Mitigating Exposure Bias in Task-Oriented Dialogscited by 1
8 more
  1. 2022CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Trackingcited by 1
  2. 2023Multijugate Dual Learning for Low-Resource Task-Oriented Dialogue Systemcited by 1
  3. 2024TA&AT: Enhancing Task-Oriented Dialog with Turn-Level Auxiliary Tasks and Action-Tree Based Scheduled Samplingcited by 1
  4. 2023Curricular Transfer Learning for Sentence Encoded Taskscited by 0
  5. 2024Comparing Data Augmentation Methods for End-to-End Task-Oriented Dialog Systemscited by 0
  6. 2024Training Zero-Shot Generalizable End-to-End Task-Oriented Dialog System Without Turn-level Dialog Annotationscited by 0
  7. 2025Collaborative and Proactive Management of Task-Oriented Conversationscited by 0
  8. 2026Automated evaluation of LLMs for effective machine translation of Mandarin Chinese to Englishcited by 0