SOTAVerified

Semantic Similarity

The main objective Semantic Similarity is to measure the distance between the semantic meanings of a pair of words, phrases, sentences, or documents. For example, the word “car” is more similar to “bus” than it is to “cat”. The two main approaches to measuring Semantic Similarity are knowledge-based approaches and corpus-based, distributional methods.

Source: Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection

Papers

Showing 10261050 of 1564 papers

TitleStatusHype
Wild Devs' at SemEval-2017 Task 2: Using Neural Networks to Discover Word Similarity0
Word Embedding Evaluation in Downstream Tasks and Semantic Analogies0
Word Embeddings and Validity Indexes in Fuzzy Clustering0
Word Embeddings as Metric Recovery in Semantic Spaces0
Words Blending Boxes. Obfuscating Queries in Information Retrieval using Differential Privacy0
Word Semantic Similarity for Morphologically Rich Languages0
Word to Sentence Visual Semantic Similarity for Caption Generation: Lessons Learned0
Word Vector Space Specialisation0
YiSi - a Unified Semantic MT Quality Evaluation and Estimation Metric for Languages with Different Levels of Available Resources0
Zero-shot Event Causality Identification with Question Answering0
Zero-Shot Learning via Semantic Similarity Embedding0
Zero-shot Learning with Minimum Instruction to Extract Social Determinants and Family History from Clinical Notes using GPT Model0
Zero-Shot Text Matching for Automated Auditing using Sentence Transformers0
A new approach for measuring semantic similarity of ontology concepts using dynamic programming0
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs0
Enhancing Adversarial Text Attacks on BERT Models with Projected Gradient Descent0
Enhancing Semantic Similarity Understanding in Arabic NLP with Nested Embedding Learning0
A Semi-supervised Multi-channel Graph Convolutional Network for Query Classification in E-commerce0
TempRetriever: Fusion-based Temporal Dense Passage Retrieval for Time-Sensitive Questions0
Towards Automated Situation Awareness: A RAG-Based Framework for Peacebuilding Reports0
AI-enhanced semantic feature norms for 786 concepts0
Evaluations at Work: Measuring the Capabilities of GenAI in Use0
3D Compositional Zero-shot Learning with DeCompositional Consensus0
A 2D Semantic-Aware Position Encoding for Vision Transformers0
A bilingual approach to specialised adjectives through word embeddings in the karstology domain0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F193.38Unverified
2SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F191.51Unverified
3SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F190.69Unverified
4BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F189.16Unverified
5BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F189.12Unverified
#ModelMetricClaimedVerifiedStatus
1BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.75Unverified
2SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3Unverified
3SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3Unverified
4BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F186.8Unverified
5BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F184.21Unverified
#ModelMetricClaimedVerifiedStatus
1Doc2VecCMSE0.31Unverified
2LSTM (Tai et al., 2015)MSE0.28Unverified
3Bidirectional LSTM (Tai et al., 2015)MSE0.27Unverified
4combine-skip (Kiros et al., 2015)MSE0.27Unverified
5Dependency Tree-LSTM (Tai et al., 2015)MSE0.25Unverified
#ModelMetricClaimedVerifiedStatus
1BioLinkBERT (large)Pearson Correlation0.94Unverified
2BioLinkBERT (base)Pearson Correlation0.93Unverified
3NCBI_BERT(base) (P+M)Pearson Correlation0.92Unverified
#ModelMetricClaimedVerifiedStatus
1MacBERT-largeMacro F185.6Unverified
#ModelMetricClaimedVerifiedStatus
1CharacterBERT (base, medical, ensemble)Pearson Correlation85.62Unverified
#ModelMetricClaimedVerifiedStatus
1NCBI_BERT(base) (P+M)Pearson Correlation0.85Unverified