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

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Showing 1201–1250 of 1564 papers

TitleStatusHype
Bringing Semantics into Focus Using Visual Abstraction—0
Brotherhood at WMT 2024: Leveraging LLM-Generated Contextual Conversations for Cross-Lingual Image Captioning—0
BUAP: Lexical and Semantic Similarity for Cross-lingual Textual Entailment—0
Building a Synthetic Biomedical Research Article Citation Linkage Corpus—0
Building Interpretable and Reliable Open Information Retriever for New Domains Overnight—0
Building Lexical Vector Representations from Concept Definitions—0
Building RadiologyNET: Unsupervised annotation of a large-scale multimodal medical database—0
Building Semantic Grams of Human Knowledge—0
Building Static Embeddings from Contextual Ones: Is It Useful for Building Distributional Thesauri?—0
Bundle Optimization for Multi-aspect Embedding—0
Calculating Semantic Similarity between Academic Articles using Topic Event and Ontology—0
Can GPT models Follow Human Summarization Guidelines? Evaluating ChatGPT and GPT-4 for Dialogue Summarization—0
Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering—0
Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network—0
CAT: Cross-Attention Transformer for One-Shot Object Detection—0
Category-Adaptive Label Discovery and Noise Rejection for Multi-label Image Recognition with Partial Positive Labels—0
Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces—0
CausalRAG: Integrating Causal Graphs into Retrieval-Augmented Generation—0
Center-wise Local Image Mixture For Contrastive Representation Learning—0
Character Set Construction for Chinese Language Learning—0
CIMON: Towards High-quality Hash Codes—0
ClaC: Semantic Relatedness of Words and Phrases—0
Classification of Semantic Paraphasias: Optimization of a Word Embedding Model—0
Classifying Verses of the Quran using Doc2vec—0
Classifying Wikipedia in a fine-grained hierarchy: what graphs can contribute—0
Class-Similarity Based Label Smoothing for Confidence Calibration—0
CLISTER : A Corpus for Semantic Textual Similarity in French Clinical Narratives—0
Cluster Analysis with Deep Embeddings and Contrastive Learning—0
Clustering Prominent People and Organizations in Topic-Specific Text Corpora—0
ClusterLog: Clustering Logs for Effective Log-based Anomaly Detection—0
CNGL-CORE: Referential Translation Machines for Measuring Semantic Similarity—0
Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension—0
Code Clone Detection based on Event Embedding and Event Dependency—0
CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings—0
Cognitively Motivated Distributional Representations of Meaning—0
Column sampling based discrete supervised hashing—0
Combinaison d'information visuelle, conceptuelle, et contextuelle pour la construction automatique de hierarchies semantiques adaptees a l'annotation d'images—0
Combining Contrastive Learning and Knowledge Graph Embeddings to develop medical word embeddings for the Italian language—0
Combining Structured and Unstructured Knowledge in an Interactive Search Dialogue System—0
Combining Word Embeddings and N-grams for Unsupervised Document Summarization—0
Common Variable Learning and Invariant Representation Learning using Siamese Neural Networks—0
Community Search in Time-dependent Road-social Attributed Networks—0
Comparing scalable strategies for generating numerical perspectives—0
Comparison of Paragram and GloVe Results for Similarity Benchmarks—0
Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation—0
Conjuring Semantic Similarity—0
Connecting the Dots: Inferring Patent Phrase Similarity with Retrieved Phrase Graphs—0
Connecting the Dots: Leveraging Spatio-Temporal Graph Neural Networks for Accurate Bangla Sign Language Recognition—0
Conservative Bias in Large Language Models: Measuring Relation Predictions—0
Consistency of Responses and Continuations Generated by Large Language Models on Social Media—0
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All datasetsAnnotated corpus for semantic similarity of clinical trial outcomes (expanded corpus)Annotated corpus for semantic similarity of clinical trial outcomes (original corpus)SICKBIOSSESCHIP-STSClinicalSTSMedSTS

Benchmark Results

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