https://github.com/google-research/task-oriented-dialogue
Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (6.8%) to scientific vocabulary
Keywords from Contributors
Repository
Basic Info
- Host: GitHub
- Owner: google-research
- License: apache-2.0
- Language: Python
- Default Branch: main
- Size: 16.8 MB
Statistics
- Stars: 69
- Watchers: 7
- Forks: 23
- Open Issues: 7
- Releases: 0
Metadata Files
README.md
Task Oriented Dialogue
Repository for all open-sourced task oriented dialogue (TOD) research at Google.
This is not an officially supported Google product. All resources in this repository are provided "AS IS" without any warranty, express or implied. Google disclaims all liability for any damages, direct or indirect, resulting from their use.
Updates
09/16/2024 - Open source the AnyTOD dataset. Sorry for the delay :)
03/28/2023 - Open source the STARv2 dataset. Code for the AnyTOD paper to be open-sourced soon.
04/12/2022 - Open source the D3ST and SDT papers.
04/04/2022 - Generalize this repository for all task-oriented dialogue research being purused at Google. Originally, this repository held projects related to the SGD dataset.
Papers in this Repository
end2end:anytod: AnyTOD: A Programmable Task-Oriented Dialog System (Zhao et. al, 2022)
generation: Template Guided Text Generation (Kale et. al, 2020)state_tracking:d3st: Description-Driven Dialogue State Tracking (Zhao et. al, 2022)sdt: Show Don't Tell (Gupta et. al, 2022)
starv2: STARv2 datset (Zhao et. al, 2022)
Other Work
- Schema-Guided Dialogue Dataset (Rastogi et. al, 2020)
- The source code for the baseline model released in SGD paper can be found here.
- The Schema-Guided State Tracking track in the 8th DSTC focussed on improving the baseline model for LU and DST. The participants were able to significantly improve the performance of the baseline model while reducing the gap in performance between seen and unseen APIs. More details about the competition and the submissions may be found in the overview paper.
Owner
- Name: Google Research
- Login: google-research
- Kind: organization
- Location: Earth
- Website: https://research.google
- Repositories: 226
- Profile: https://github.com/google-research
GitHub Events
Total
- Watch event: 6
- Fork event: 1
Last Year
- Watch event: 6
- Fork event: 1
Committers
Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Jeffrey Zhao | j****o@g****m | 8 |
| Google Research | n****y@g****m | 8 |
| Abhinav Rastogi | a****t@g****m | 4 |
| Harrison Lee | h****e@g****m | 2 |
| Yilei Yang | y****g@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 9
- Total pull requests: 3
- Average time to close issues: 2 months
- Average time to close pull requests: 16 minutes
- Total issue authors: 7
- Total pull request authors: 2
- Average comments per issue: 1.33
- Average comments per pull request: 2.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 2
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- shermansiu (3)
- gyunggyung (1)
- cathyxl (1)
- dharakyu (1)
- buiminhptit (1)
- pietrolesci (1)
- WeixuanZ (1)
Pull Request Authors
- copybara-service[bot] (2)
- WeixuanZ (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- absl-py >=0.7.0
- t5 *
- tensorflow >=2.3.1
- absl-py *
- tensorflow *
- absl-py *
- tensorflow *
- absl-py *
- ordered-set *
- tensorflow *