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STS

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Showing 176–200 of 334 papers

TitleStatusHype
Stratified and Time-aware Sampling based Adaptive Ensemble Learning for Streaming Recommendations—0
Streaming Parrotron for on-device speech-to-speech conversion—0
Structural-Aware Sentence Similarity with Recursive Optimal Transport—0
Structure-aware Sentence Encoder in Bert-Based Siamese Network—0
STS-CCL: Spatial-Temporal Synchronous Contextual Contrastive Learning for Urban Traffic Forecasting—0
STS Classification with Dual-stream CNN—0
STS-korpus: A Sign Language Web Corpus Tool for Teaching and Public Use—0
STS MICCAI 2023 Challenge: Grand challenge on 2D and 3D semi-supervised tooth segmentation—0
STS: Surround-view Temporal Stereo for Multi-view 3D Detection—0
STS-UHH at SemEval-2017 Task 1: Scoring Semantic Textual Similarity Using Supervised and Unsupervised Ensemble—0
SXUCFN-Core: STS Models Integrating FrameNet Parsing Information—0
TA-SBERT: Token Attention Sentence-BERT for Improving Sentence Representation—0
Task-Oriented Intrinsic Evaluation of Semantic Textual Similarity—0
TexIm FAST: Text-to-Image Representation for Semantic Similarity Evaluation using Transformers—0
Text Encoders Lack Knowledge: Leveraging Generative LLMs for Domain-Specific Semantic Textual Similarity—0
The role of temporal cortex in the control of attention—0
Tiantianzhu7:System Description of Semantic Textual Similarity (STS) in the SemEval-2012 (Task 6)—0
Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs—0
Toward an Effective Theory of Neurodynamics: Topological Supersymmetry Breaking, Network Coarse-Graining, and Instanton Interaction—0
Training Robust Spiking Neural Networks with ViewPoint Transform and SpatioTemporal Stretching—0
TransAug: Translate as Augmentation for Sentence Embeddings—0
Transfer to a Low-Resource Language via Close Relatives: The Case Study on Faroese—0
Transformer models as an efficient replacement for statistical test suites to evaluate the quality of random numbers—0
Two-Level Supervised Contrastive Learning for Response Selection in Multi-Turn Dialogue—0
Two-Level Supervised Contrastive Learning for Response Selection in Multi-Turn Dialogue—0
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