Methods › General › Self-Training Methods › self-mem + new data

self-mem + new data

1 paper tagged archive 2025-07-28

Introduced by Hoang-Thang Ta in Self-training from Self-memory in Data-to-text Generation

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

The training contains two steps. The first step is to train data for creating the T2D and D2T models. Then, in the second step, use these models to infer self-memory for self-training the D2T model. Then, the training takes self-memory and new data for self-training the D2T model but not the T2D model.

PaperSource

Papers archive 2025-07-28

1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

3 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Continual Learning1
Data-to-Text Generation1
Text Generation1

Usage over time archive 2025-07-28

Papers per year tagged with self-mem + new data: 2024 to 2024, peak 1 1 0 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Self-Training Methods

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