MSW-NTM: A Spherical Wasserstein Autoencoder for Multimodal Neural Topic Modeling with LLM-Guided Topic Refinement.

Chris Buckley|Dayu Guo|Zhiwen Luo|Ryen W. White|Wentao Fan|Nizar Bouguila|Ryen W. White|Wentao Fan


Anthology ID:DBLP:conf/sigir/GuoLBF26
Volume:Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2026, MelbourneVICAustralia, July 20-24, 2026
Year:2026
Venue:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Publisher:ACM
Pages:3759-3763
URL:https://doi.org/10.1145/3805712.3809878
DOI:https://doi.org/10.1145/3805712.3809878
DBLP:conf/sigir/GuoLBF26
BibTeX:
@inproceedings{buckley-2026-mswntm, author = {Chris Buckley and Dayu Guo and Zhiwen Luo and Ryen W. White and Wentao Fan and Nizar Bouguila and Ryen W. White and Wentao Fan}, editor = {Hannah Bast and Alistair Moffat and Falk Scholer and Marc Najork and Min Zhang and Hannah Bast and Marc Najork and Min Zhang}, title = {{MSW-NTM: A Spherical Wasserstein Autoencoder for Multimodal Neural Topic Modeling with LLM-Guided Topic Refinement}}, booktitle = {{Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2026, MelbourneVICAustralia, July 20-24, 2026}}, pages = {3759--3763}, publisher = {ACM}, year = {2026}, url = {https://doi.org/10.1145/3805712.3809878}, doi = {https://doi.org/10.1145/3805712.3809878} }