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 526–550 of 1564 papers

TitleStatusHype
Deep Contrastive Multi-view Clustering under Semantic Feature Guidance—0
Is Cosine-Similarity of Embeddings Really About Similarity?—0
Persona Extraction Through Semantic Similarity for Emotional Support Conversation Generation—0
SAM-PD: How Far Can SAM Take Us in Tracking and Segmenting Anything in Videos by Prompt DenoisingCode0
GPTSee: Enhancing Moment Retrieval and Highlight Detection via Description-Based Similarity Features—0
API Is Enough: Conformal Prediction for Large Language Models Without Logit-Access—0
Semantic Text Transmission via Prediction with Small Language Models: Cost-Similarity Trade-off—0
PaECTER: Patent-level Representation Learning using Citation-informed Transformers—0
BiVRec: Bidirectional View-based Multimodal Sequential Recommendation—0
Investigating Continual Pretraining in Large Language Models: Insights and Implications—0
Sequential Visual and Semantic Consistency for Semi-supervised Text Recognition—0
The Impact of Word Splitting on the Semantic Content of Contextualized Word RepresentationsCode0
Efficient data selection employing Semantic Similarity-based Graph Structures for model training—0
Semantic Mirror Jailbreak: Genetic Algorithm Based Jailbreak Prompts Against Open-source LLMs—0
On Defining Smart Cities using Transformer Neural Networks—0
UMBCLU at SemEval-2024 Task 1A and 1C: Semantic Textual Relatedness with and without machine translationCode0
Semantic Textual Similarity Assessment in Chest X-ray Reports Using a Domain-Specific Cosine-Based MetricCode0
Reasoning before Comparison: LLM-Enhanced Semantic Similarity Metrics for Domain Specialized Text Analysis—0
OrderBkd: Textual backdoor attack through repositioningCode0
Large Language Model Augmented Exercise Retrieval for Personalized Language Learning—0
Multi-Lingual Malaysian Embedding: Leveraging Large Language Models for Semantic Representations—0
HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on TextCode0
In-Context Learning for Few-Shot Nested Named Entity Recognition—0
Enhancing End-to-End Multi-Task Dialogue Systems: A Study on Intrinsic Motivation Reinforcement Learning Algorithms for Improved Training and Adaptability—0
Autoencoder-Based Domain Learning for Semantic Communication with Conceptual Spaces—0
Show:102550
← PrevPage 22 of 63Next →
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 cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
3SciBERT uncased (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