What role does sequence-to-sequence modeling play in generating cohesive text in conversational AI

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Can you tell me what role does sequence-to-sequence modeling play in generating cohesive text in conversational AI?
Nov 21 in Generative AI by Ashutosh
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1 answer to this question.

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Sequence-to-sequence modeling plays an important role in generating cohesive text in conversational AI by: 

  • Ensuring cohesion by mapping input sequences (user queries) to output sequences (responses) while maintaining context and logical flow. 
  • Models like Transformer-based Seq2Seq (e.g., T5, BART) handle complex dependencies for coherent responses.

Here is the code snippet you can refer to:

In the above code, we capture context, generate cohesive replies, and handle long-range dependencies for multi-turn dialogue coherence.

Hence, sequence-to-sequence modeling plays an important role in generating cohesive text in conversational AI.

answered Nov 21 by anant dubey

edited Nov 21 by Ashutosh

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