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 151175 of 1564 papers

TitleStatusHype
A Comprehensive Framework for Semantic Similarity Analysis of Human and AI-Generated Text Using Transformer Architectures and Ensemble Techniques0
Rethinking the Sample Relations for Few-Shot ClassificationCode7
Sequence Spreading-Based Semantic Communication Under High RF Interference0
LegalGuardian: A Privacy-Preserving Framework for Secure Integration of Large Language Models in Legal Practice0
MedFILIP: Medical Fine-grained Language-Image Pre-trainingCode1
Evaluating GenAI for Simplifying Texts for Education: Improving Accuracy and Consistency for Enhanced Readability0
Consistency of Responses and Continuations Generated by Large Language Models on Social Media0
Contextual ASR Error Handling with LLMs Augmentation for Goal-Oriented Conversational AI0
GeAR: Generation Augmented Retrieval0
Universal Features Guided Zero-Shot Category-Level Object Pose Estimation0
Anchor-Aware Similarity Cohesion in Target Frames Enables Predicting Temporal Moment Boundaries in 2DCode0
Harnessing Frozen Unimodal Encoders for Flexible Multimodal AlignmentCode0
ProtCLIP: Function-Informed Protein Multi-Modal Learning0
Multiple References with Meaningful Variations Improve Literary Machine Translation0
Reasoning to Attend: Try to Understand How <SEG> Token WorksCode2
DiffSim: Taming Diffusion Models for Evaluating Visual SimilarityCode1
HashAttention: Semantic Sparsity for Faster Inference0
DuSSS: Dual Semantic Similarity-Supervised Vision-Language Model for Semi-Supervised Medical Image SegmentationCode1
Quantifying Positional Biases in Text Embedding ModelsCode0
Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training DataCode1
Single-View Graph Contrastive Learning with Soft Neighborhood AwarenessCode0
Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource LanguagesCode0
Generating Knowledge Graphs from Large Language Models: A Comparative Study of GPT-4, LLaMA 2, and BERT0
SiReRAG: Indexing Similar and Related Information for Multihop Reasoning0
Detecting Redundant Health Survey Questions Using Language-agnostic BERT Sentence Embedding (LaBSE)0
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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