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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 701–725 of 1564 papers

TitleStatusHype
DeepTrax: Embedding Graphs of Financial Transactions—0
Automatic Visual Theme Discovery from Joint Image and Text Corpora—0
Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval—0
Automatic Real-word Error Correction in Persian Text—0
Analyzing the impact of climate change on critical infrastructure from the scientific literature: A weakly supervised NLP approach—0
Adversarial Contrastive Learning by Permuting Cluster Assignments—0
A Classification-Based Approach to Cognate Detection Combining Orthographic and Semantic Similarity Information—0
TempRetriever: Fusion-based Temporal Dense Passage Retrieval for Time-Sensitive Questions—0
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs—0
DeepRTL: Bridging Verilog Understanding and Generation with a Unified Representation Model—0
DeepPurple: Lexical, String and Affective Feature Fusion for Sentence-Level Semantic Similarity Estimation—0
DeepPurple: Estimating Sentence Semantic Similarity using N-gram Regression Models and Web Snippets—0
Automatic Difficulty Classification of Arabic Sentences—0
Deep Lifelong Cross-modal Hashing—0
Analysis of Word Embeddings Using Fuzzy Clustering—0
Advancing Large Language Models for Spatiotemporal and Semantic Association Mining of Similar Environmental Events—0
Deep Contrastive Multi-view Clustering under Semantic Feature Guidance—0
Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions—0
Xu: An Automated Query Expansion and Optimization Tool—0
Analogies in Complex Verb Meaning Shifts: the Effect of Affect in Semantic Similarity Models—0
Decoding Emotional Experiences in Dyadic Conversations of Married Couples: Leveraging Semantic Similarity through Sentence Embedding—0
Automated Feedback Loops to Protect Text Simplification with Generative AI from Information Loss—0
An\'alise de Medidas de Similaridade Sem\^antica na Tarefa de Reconhecimento de Implica \~ao Textual (Analysis of Semantic Similarity Measures in the Recognition of Textual Entailment Task)[In Portuguese]—0
A Discriminative Vectorial Framework for Multi-modal Feature Representation—0
DebCSE: Rethinking Unsupervised Contrastive Sentence Embedding Learning in the Debiasing Perspective—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