Papers with noise filtering

2 papers
Enhancing Foundation Models in Transaction Understanding with LLM-based Sentence Embeddings (2025.emnlp-industry)

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Challenge: Existing foundation models for tabular transactional data rely on index-based representations for categorical merchant fields.
Approach: They propose a framework that uses LLM-generated embeddings as semantic initializations for lightweight transaction models.
Outcome: The proposed framework improves performance on large transaction datasets.
Denoising Bottleneck with Mutual Information Maximization for Video Multimodal Fusion (2023.acl-long)

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Challenge: Prior denoising methods suppress redundant and noisy information at risk of losing critical information.
Approach: They propose a denoising bottleneck fusion model for fine-grained video multimodal fusion . they employ a bottleneck mechanism to filter out noise and redundancy with a restrained receptive field .
Outcome: The proposed model improves on state-of-the-art video multimodal fusion benchmarks.

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