Delete, Retrieve, Generate: a Simple Approach to Sentiment and Style Transfer
Abstract
Domain fit: AI-adjacent · Paper appears method- or tooling-adjacent to AI workflows with partial ecosystem coverage.
Juncen Li, Robin Jia, He He, Percy Liang. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). 2018.
Results and benchmarks
Juncen Li, Robin Jia, He He, Percy Liang.
Benchmark evidence is limited
Evidence graph: 2 refs, 1 links.
Utility signals: depth 45/100, grounding 58/100, status medium.
Implementation
No direct implementation yet
Maintained implementation evidence is not confirmed for this paper yet.
Use the implementation status and reproduction sections for the current action plan.
No verified maintained repo yet
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- No direct maintained implementation was found. Use the paper PDF and citation graph to design a baseline reproduction.
- Start from related paper: “Transforming” Delete, Retrieve, Generate Approach for Controlled Text Style Transfer.
- Track assumptions and missing details in an experiment log before coding.
Time to first repro: a few days
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- Estimate is based on paper-only reproduction flow
Reproduction readiness
No repo
No verified implementation available
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Hardware requirements
- Expect multi-day setup/compute for meaningful reproduction based on current guidance.
Validation caveat
Hugging Face artifacts
No trustworthy direct or curated related Hugging Face artifacts were found yet. Use targeted searches to quickly locate candidate models, datasets, and demos.
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Research context
476
Citations
24
References
Tasks
Computer science, Style (visual arts), Simple (philosophy), Computational linguistics, Sentiment analysis, Volume (thermodynamics), Association (psychology), Transfer (computing)
Methods
text retrieval
Domains
Artificial intelligence, Natural language processing
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