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Found 6 papers, 0 papers with code
Never Lost in the Middle: Improving Large Language Models via Attention Strengthening Question Answering
While large language models (LLMs) are equipped with longer text input capabilities than before, they are struggling to seek correct information in long contexts.
Learning Spatial and Temporal Variations for 4D Point Cloud Segmentation
We design a temporal variation-aware interpolation module and a temporal voxel-point refiner to capture the temporal variation in the 4D point cloud.
Unsupervised Mismatch Localization in Cross-Modal Sequential Data with Application to Mispronunciations Localization
Content mismatch usually occurs when data from one modality is translated to another, e. g. language learners producing mispronunciations (errors in speech) when reading a sentence (target text) aloud.
FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging
FoodAI has made food logging convenient, aiding smart consumption and a healthy lifestyle.
Semi-supervised Deep Generative Modelling of Incomplete Multi-Modality Emotional Data
To address the missing-modality problem, we further extend our semi-supervised multi-view model to deal with incomplete data, where a missing view is treated as a latent variable and integrated out during inference.
A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Users
In this paper, we propose a latent probabilistic generative model called LSARS to mimic the decision-making process of users' check-in activities both in home-town and out-of-town scenarios by adapting to user interest drift and crowd sentiments, which can learn location-aware and sentiment-aware individual interests from the contents of spatial items and user reviews.
