Papers with clustering module
Learning to Rank Question-Answer Pairs Using Hierarchical Recurrent Encoder with Latent Topic Clustering (N18-1)
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| Challenge: | Existing models for sentence pair ranking are based on hierarchical recurrent neural network and latent topic clustering module. |
| Approach: | They propose a hierarchical recurrent neural network and latent topic clustering module to adapt a recursive hierarchic neural network to rank candidate answers. |
| Outcome: | The proposed model shows small performance degradations in longer text comprehension compared to current models which suffer from it. |
SHIFT: Selected Helpful Informative Frame for Video-guided Machine Translation (2025.emnlp-main)
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| Challenge: | Video-guided machine translation (VMT) aims to improve translation quality by integrating contextual information from paired short video clips. |
| Approach: | They propose a plug-and-play framework for video-guided machine translation with multimodal large language models. |
| Outcome: | The proposed framework improves performance of MLLMs while reducing computational cost. |
Towards Speaker Verification for Crowdsourced Speech Collections (2022.lrec-1)
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| Challenge: | Existing methods to detect low quality work do not address the correctness of the data. |
| Approach: | They propose an unsupervised method for measuring speaker metadata plausibility of a collection, i.e., evaluating the match (or lack thereof) between contributors and speakers. |
| Outcome: | The proposed method shows high precision in automatically classifying contributor alignment (>0.94). |