Papers with multimodality problem

2 papers
Benchmarking Diffusion Models for Machine Translation (2024.eacl-srw)

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Challenge: Diffusion models have shown great potential on many generative tasks, but their application to natural language processing (NLP) is still a less explored direction.
Approach: They adapt two diffusion-based text generation models, Diffusion-LM and DiffuSeq, to perform machine translation.
Outcome: The proposed models struggle more on long-range dependencies than other models.
POS-Constrained Parallel Decoding for Non-autoregressive Generation (2021.acl-long)

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Challenge: Existing non-autoregressive generation systems face multimodality problem due to conditionally independent decoding.
Approach: They propose to incorporate linguistic structure into NAG inference instead of teacher AG . they propose a method that provides a specific POS sequence to constrain the NAG model .
Outcome: The proposed method improves NAG models on four text generation tasks to a greater extent compared to knowledge distillation.

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