Sequence-to-Sequence Model (Seq2Seq)
Definition
Seq2Seq models convert a sequence of inputs into a suitable sequence of outputs.
A model architecture that transforms an input sequence into an output sequence, often with an encoder and decoder.
Simply explained
One word sequence goes in, another comes out, for example in translating a sentence.
Why it matters in practice
The term helps to select, develop, evaluate AI systems in a well-founded manner and realistically assess their technical risks.
Example from business
A model translates a German sentence into an English word sequence.
Limits and pitfalls
- Expecting long sequences without attention or confusing teacher forcing and inference conditions.
Origin & history
Sutskever, Vinyals, and Le published a seminal neural Seq2Seq method in 2014.
Use in mid-sized companies
- Possible example: A model translates a German sentence into an English word sequence.
Frequently asked questions
What does sequence-to-sequence model (Seq2Seq) mean?
A model architecture that transforms an input sequence into an output sequence, often with an encoder and decoder. What mistakes should be avoided? Expecting long sequences without attention or confusing teacher forcing and inference conditions.
Sources
Source checked on 10.10.2026. Editorial application examples are hypothetical; no evidence of real customer results.
Editorially reviewed on: