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Showing 251–300 of 334 papers

TitleStatusHype
Neobility at SemEval-2017 Task 1: An Attention-based Sentence Similarity Model—0
Neural association between musical features and shared emotional perception while movie-watching: fMRI study—0
Neural representation of action sequences: how far can a simple snippet-matching model take us?—0
Noisy Text Data: Achilles’ Heel of BERT—0
Non-Autoregressive Neural Dialogue Generation—0
Non-Interchangeability between Heart Rate Variability and Pulse Rate Variability During Supine-to-Stand Tests—0
On Adversarial Examples for Biomedical NLP Tasks—0
On the Dimensionality of Sentence Embeddings—0
On the (im)possibility of sustainable artificial intelligence. Why it does not make sense to move faster when heading the wrong way—0
OPI-JSA at SemEval-2017 Task 1: Application of Ensemble learning for computing semantic textual similarity—0
Parallel Bayesian Optimization Using Satisficing Thompson Sampling for Time-Sensitive Black-Box Optimization—0
Paraphrase Generation as Unsupervised Machine Translation—0
Patterns of social mobility across social groups in India—0
pH/T duality - wall properties and time evolution of plant cells—0
Predicting Distant Metastases in Soft-Tissue Sarcomas from PET-CT scans using Constrained Hierarchical Multi-Modality Feature Learning—0
Predicting the Semantic Textual Similarity with Siamese CNN and LSTM—0
PromptBERT: Improving BERT Sentence Embeddings with Prompts—0
PropNet: a White-Box and Human-Like Network for Sentence Representation—0
ptt5-v2: A Closer Look at Continued Pretraining of T5 Models for the Portuguese Language—0
PurdueNLP at SemEval-2017 Task 1: Predicting Semantic Textual Similarity with Paraphrase and Event Embeddings—0
Rethinking STS and NLI in Large Language Models—0
Revealing the Blind Spot of Sentence Encoder Evaluation by HEROS—0
Robots Enact Malignant Stereotypes—0
RTM at SemEval-2016 Task 1: Predicting Semantic Similarity with Referential Translation Machines and Related Statistics—0
RTM at SemEval-2017 Task 1: Referential Translation Machines for Predicting Semantic Similarity—0
Rule-based vs. Neural Net Approaches to Semantic Textual Similarity—0
Seed-to-Seed: Image Translation in Diffusion Seed Space—0
Self-Adaptive Reconstruction with Contrastive Learning for Unsupervised Sentence Embeddings—0
Learning Semantic Textual Similarity from ConversationsCode0
Unmasking the Role of Remote Sensors in Comfort, Energy and Demand ResponseCode0
Unsupervised hard Negative Augmentation for contrastive learningCode0
Linguistically Conditioned Semantic Textual SimilarityCode0
Unsupervised Natural Language Inference via Decoupled Multimodal Contrastive LearningCode0
Contrastive Learning in Distilled ModelsCode0
ConCSE: Unified Contrastive Learning and Augmentation for Code-Switched EmbeddingsCode0
JCSE: Contrastive Learning of Japanese Sentence Embeddings and Its ApplicationsCode0
Instance Smoothed Contrastive Learning for Unsupervised Sentence EmbeddingCode0
Are ELECTRA's Sentence Embeddings Beyond Repair? The Case of Semantic Textual SimilarityCode0
Don't Judge a Language Model by Its Last Layer: Contrastive Learning with Layer-Wise Attention PoolingCode0
Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective DistillationCode0
Space Decomposition for Sentence EmbeddingCode0
Improving Sentence Embeddings with Automatic Generation of Training Data Using Few-shot ExamplesCode0
Improving Multi-lingual Alignment Through Soft Contrastive LearningCode0
Missing Data Reconstruction in Remote Sensing image with a Unified Spatial-Temporal-Spectral Deep Convolutional Neural NetworkCode0
Enhancing Text Generation with Cooperative TrainingCode0
Model Comparison for Semantic GroupingCode0
Improving Contrastive Learning of Sentence Embeddings with Focal-InfoNCECode0
Self-supervised contrastive learning unveils cortical folding pattern linked to prematurityCode0
Graph Component Contrastive Learning for Concept Relatedness EstimationCode0
Characterizing the limits of human stability during motion: perturbative experiment validates a model-based approach for the Sit-to-Stand taskCode0
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