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 151–200 of 1564 papers

TitleStatusHype
A Comprehensive Framework for Semantic Similarity Analysis of Human and AI-Generated Text Using Transformer Architectures and Ensemble Techniques—0
Rethinking the Sample Relations for Few-Shot ClassificationCode7
Sequence Spreading-Based Semantic Communication Under High RF Interference—0
LegalGuardian: A Privacy-Preserving Framework for Secure Integration of Large Language Models in Legal Practice—0
MedFILIP: Medical Fine-grained Language-Image Pre-trainingCode1
Evaluating GenAI for Simplifying Texts for Education: Improving Accuracy and Consistency for Enhanced Readability—0
Consistency of Responses and Continuations Generated by Large Language Models on Social Media—0
Contextual ASR Error Handling with LLMs Augmentation for Goal-Oriented Conversational AI—0
GeAR: Generation Augmented Retrieval—0
Universal Features Guided Zero-Shot Category-Level Object Pose Estimation—0
Harnessing Frozen Unimodal Encoders for Flexible Multimodal AlignmentCode0
Anchor-Aware Similarity Cohesion in Target Frames Enables Predicting Temporal Moment Boundaries in 2DCode0
ProtCLIP: Function-Informed Protein Multi-Modal Learning—0
Multiple References with Meaningful Variations Improve Literary Machine Translation—0
Reasoning to Attend: Try to Understand How <SEG> Token WorksCode2
DiffSim: Taming Diffusion Models for Evaluating Visual SimilarityCode1
HashAttention: Semantic Sparsity for Faster Inference—0
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 BERT—0
SiReRAG: Indexing Similar and Related Information for Multihop Reasoning—0
Detecting Redundant Health Survey Questions Using Language-agnostic BERT Sentence Embedding (LaBSE)—0
Human Variability vs. Machine Consistency: A Linguistic Analysis of Texts Generated by Humans and Large Language Models—0
VidHalluc: Evaluating Temporal Hallucinations in Multimodal Large Language Models for Video Understanding—0
Interpretable Company Similarity with Sparse Autoencoders—0
TSCheater: Generating High-Quality Tibetan Adversarial Texts via Visual SimilarityCode0
Quantifying perturbation impacts for large language models—0
Vid-Morp: Video Moment Retrieval Pretraining from Unlabeled Videos in the WildCode1
RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable DataCode1
Generative Semantic Communication for Joint Image Transmission and Segmentation—0
Isolating authorship from content with semantic embeddings and contrastive learning—0
In-Context Experience Replay Facilitates Safety Red-Teaming of Text-to-Image Diffusion Models—0
FAST-Splat: Fast, Ambiguity-Free Semantics Transfer in Gaussian Splatting—0
Advancing Large Language Models for Spatiotemporal and Semantic Association Mining of Similar Environmental Events—0
Membership Inference Attack against Long-Context Large Language Models—0
Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data—0
Squeezed Attention: Accelerating Long Context Length LLM InferenceCode2
Securing from Unseen: Connected Pattern Kernels (CoPaK) for Zero-Day Intrusion Detection—0
Leveraging LLMs to Enable Natural Language Search on Go-to-market Platforms—0
Semantic-Aware Resource Management for C-V2X Platooning via Multi-Agent Reinforcement LearningCode1
A Comparative Study of Recent Large Language Models on Generating Hospital Discharge Summaries for Lung Cancer Patients—0
Fine-Grained Guidance for Retrievers: Leveraging LLMs' Feedback in Retrieval-Augmented Generation—0
Continual Audio-Visual Sound SeparationCode0
HACD: Harnessing Attribute Semantics and Mesoscopic Structure for Community DetectionCode0
NLP and Education: using semantic similarity to evaluate filled gaps in a large-scale Cloze test in the classroom—0
CmdCaliper: A Semantic-Aware Command-Line Embedding Model and Dataset for Security ResearchCode1
FedDTPT: Federated Discrete and Transferable Prompt Tuning for Black-Box Large Language Models—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 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