Transformers

Temporal-Channel Modeling in Multi-head Self-Attention for Synthetic Speech Detection Interspeech 2024 Temporal Correlation Vision Transformer for Video Person Re-Identification AAAI 2024 Temporal Graph Contrastive Learning for Sequential Recommendation AAAI 2024 Tending Towards Stability: Convergence Challenges in Small Language Models EMNLP 2024 TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts ICLR 2024 Testing the limits of logical reasoning in neural and hybrid models NAACL 2024 Test-Time Domain Generalization for Face Anti-Spoofing CVPR 2024 Test-Time Model Adaptation with Only Forward Passes ICML 2024 TE-TAD: Towards Full End-to-End Temporal Action Detection via Time-Aligned Coordinate Expression CVPR 2024 Text2HOI: Text-guided 3D Motion Generation for Hand-Object Interaction CVPR 2024 Text-Based Occluded Person Re-identification via Multi-Granularity Contrastive Consistency Learning AAAI 2024 Text Diffusion Model with Encoder-Decoder Transformers for Sequence-to-Sequence Generation NAACL 2024 TextGT: A Double-View Graph Transformer on Text for Aspect-Based Sentiment Analysis AAAI 2024 Text-Guided Attention is All You Need for Zero-Shot Robustness in Vision-Language Models NeurIPS 2024 Text-Guided Molecule Generation with Diffusion Language Model AAAI 2024 Text-to-Song: Towards Controllable Music Generation Incorporating Vocal and Accompaniment ACL 2024 Textual Alchemy: CoFormer for Scene Text Understanding WACV 2024 Textual Dataset Distillation via Language Model Embedding EMNLP 2024 The Audio-Visual Conversational Graph: From an Egocentric-Exocentric Perspective CVPR 2024 The Closeness of In-Context Learning and Weight Shifting for Softmax Regression NeurIPS 2024 The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains NeurIPS 2024 The Expressive Capacity of State Space Models: A Formal Language Perspective NeurIPS 2024 The Illusion of State in State-Space Models ICML 2024 The Impact of Language Adapters in Cross-Lingual Transfer for NLU EACL 2024 The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains NeurIPS 2024