Papers with reverse diffusion process
DiffusionNER: Boundary Diffusion for Named Entity Recognition (2023.acl-long)
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| Challenge: | Named Entity Recognition (NER) tasks are fundamental to many structured information extraction tasks. |
| Approach: | They propose a named entity recognition task that uses a boundary-denoising diffusion process to denoise noisy spans. |
| Outcome: | The proposed method achieves comparable or even better performance than previous state-of-the-art models on flat and nested datasets. |
Mustango: Toward Controllable Text-to-Music Generation (2024.naacl-long)
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| Challenge: | Mustango is a text-to-music system that allows music-domain-knowledge-informed text-based music generation. |
| Approach: | They propose a music-domain-knowledge-inspired text-to-music system based on diffusion that generates music with captions that include specific instructions related to chords, beats, key and tempo. |
| Outcome: | The proposed system outperforms existing models in music generation tasks. |
Generating Coherent Sequences of Visual Illustrations for Real-World Manual Tasks (2024.acl-long)
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João Bordalo, Vasco Ramos, Rodrigo Valério, Diogo Glória-Silva, Yonatan Bitton, Michal Yarom, Idan Szpektor, Joao Magalhaes
| Challenge: | Large Vision/Language Models (LVLMs) are less capable of generating accompanying image sequences. |
| Approach: | They propose a method that integrates a Latent Diffusion Model (LDM) with an LLM to generate captions to maintain semantic coherence of the sequence. |
| Outcome: | The proposed method is preferred by humans in 46.6% of the cases against 26.6% for the second best method. |