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Showing 151–175 of 334 papers

TitleStatusHype
DT\_Team at SemEval-2017 Task 1: Semantic Similarity Using Alignments, Sentence-Level Embeddings and Gaussian Mixture Model Output—0
Dual-View Distilled BERT for Sentence Embedding—0
EASE: Entity-Aware Contrastive Learning of Sentence Embedding—0
Efficient Domain Adaptation of Sentence Embeddings Using Adapters—0
Empirical Analysis of Efficient Fine-Tuning Methods for Large Pre-Trained Language Models—0
EnCBP: A New Benchmark Dataset for Finer-Grained Cultural Background Prediction in English—0
Enhancing conversational quality in language learning chatbots: An evaluation of GPT4 for ASR error correction—0
Enhancing Unsupervised Sentence Similarity Methods with Deep Contextualised Word Representations—0
Estimating Mutual Information Between Dense Word Embeddings—0
Evaluating Multimodal Interactive Agents—0
Evaluating semantic models with word-sentence relatedness—0
Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks—0
Evaluating the Utility of Model Configurations and Data Augmentation on Clinical Semantic Textual Similarity—0
Evaluation Datasets for Cross-lingual Semantic Textual Similarity—0
Evaluation of BERT and ALBERT Sentence Embedding Performance on Downstream NLP Tasks—0
Exploring Activation Patterns of Parameters in Language Models—0
Exploring Dimensionality Reduction Techniques in Multilingual Transformers—0
Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding—0
Extending Monolingual Semantic Textual Similarity Task to Multiple Cross-lingual Settings—0
Extracting Sentence Embeddings from Pretrained Transformer Models—0
FarFetched: An Entity-centric Approach for Reasoning on Textually Represented Environments—0
Fast and Discriminative Semantic Embedding—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
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