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Found 8 papers, 3 papers with code
CMATH: Cross-Modality Augmented Transformer with Hierarchical Variational Distillation for Multimodal Emotion Recognition in Conversation
Then, it introduces a hierarchical distillation framework to maintain the consistency between modality representations with different granularities.
Emotion Recognition in Conversation
Multimodal Emotion Recognition
CQIL: Inference Latency Optimization with Concurrent Computation of Quasi-Independent Layers
Empirical experiments of the proposed approach on the LLaMA models confirm that Concurrent Computation of Quasi-Independent Layers (CQIL) can reduce latency by up to 48. 3% on LLaMA-33B, while maintaining a close level of performance.
Securing Recommender System via Cooperative Training
Consequently, we put forth a Game-based Co-training Attack (GCoAttack), which frames the proposed CoAttack and TCD as a game-theoretic process, thoroughly exploring CoAttack's attack potential in the cooperative training of attack and defense.
Categorization and analysis of 14 computational methods for estimating cell potency from single-cell RNA-seq data
This review aims to provide a foundation for future benchmark studies, while also addressing the broader challenge of comparing methods that infer cellular dynamics from scRNA-seq data through various perspectives, including pseudotime trajectories, RNA velocities, and cell potency.
Using Saliency and Cropping to Improve Video Memorability
Video memorability is a measure of how likely a particular video is to be remembered by a viewer when that viewer has no emotional connection with the video content.
Polarity is all you need to learn and transfer faster
Natural intelligences (NIs) thrive in a dynamic world - they learn quickly, sometimes with only a few samples.
Towards Robust Recommender Systems via Triple Cooperative Defense
Notably, TCD adds pseudo label data instead of deleting abnormal data, which avoids the cleaning of normal data, and the cooperative training of the three models is also beneficial to model generalization.
