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 351–400 of 1564 papers

TitleStatusHype
EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Association—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
EDS-MEMBED: Multi-sense embeddings based on enhanced distributional semantic structures via a graph walk over word senses—0
Early Discovery of Emerging Entities in Persian Twitter with Semantic Similarity—0
Efficient comparison of sentence embeddings—0
DebCSE: Rethinking Unsupervised Contrastive Sentence Embedding Learning in the Debiasing Perspective—0
Accelerating LLaMA Inference by Enabling Intermediate Layer Decoding via Instruction Tuning with LITE—0
Data Driven Content Creation using Statistical and Natural Language Processing Techniques for Financial Domain—0
Data Augmentation for Voice-Assistant NLU using BERT-based Interchangeable Rephrase—0
Autoencoding Low-Resolution MRI for Semantically Smooth Interpolation of Anisotropic MRI—0
DALR: Dual-level Alignment Learning for Multimodal Sentence Representation Learning—0
Czech News Dataset for Semantic Textual Similarity—0
A multi-perspective combined recall and rank framework for Chinese procedure terminology normalization—0
Dynamic Few-Shot Learning for Knowledge Graph Question Answering—0
ECNU at SemEval-2017 Task 1: Leverage Kernel-based Traditional NLP features and Neural Networks to Build a Universal Model for Multilingual and Cross-lingual Semantic Textual Similarity—0
Czech Dataset for Semantic Similarity and Relatedness—0
Cyc3D: Fine-grained Controllable 3D Generation via Cycle Consistency Regularization—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
A Discriminative Vectorial Framework for Multi-modal Feature Representation—0
Autoencoder-Based Domain Learning for Semantic Communication with Conceptual Spaces—0
Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions—0
AuthorMist: Evading AI Text Detectors with Reinforcement Learning—0
A Multi-level Alignment Training Scheme for Video-and-Language Grounding—0
Duplicate Detection in a Knowledge Base with PIKA—0
Deep Lifelong Cross-modal Hashing—0
Analysis of Word Embeddings Using Fuzzy Clustering—0
Cross-modal Subspace Learning via Kernel Correlation Maximization and Discriminative Structure Preserving—0
DeepPurple: Estimating Sentence Semantic Similarity using N-gram Regression Models and Web Snippets—0
DeepPurple: Lexical, String and Affective Feature Fusion for Sentence-Level Semantic Similarity Estimation—0
Cross-modal Deep Metric Learning with Multi-task Regularization—0
Author-aware Aspect Topic Sentiment Model to Retrieve Supporting Opinions from Reviews—0
Cross-media Similarity Metric Learning with Unified Deep Networks—0
Cross-Media Scientific Research Achievements Retrieval Based on Deep Language Model—0
DeepTrax: Embedding Graphs of Financial Transactions—0
Automatic Visual Theme Discovery from Joint Image and Text Corpora—0
DELTA: Pre-train a Discriminative Encoder for Legal Case Retrieval via Structural Word Alignment—0
DEMO: A Statistical Perspective for Efficient Image-Text Matching—0
A Modified Word Saliency-Based Adversarial Attack on Text Classification Models—0
Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor—0
A density compensation-based path computing model for measuring semantic similarity—0
ECNU: Leveraging on Ensemble of Heterogeneous Features and Information Enrichment for Cross Level Semantic Similarity Estimation—0
Efficient data selection employing Semantic Similarity-based Graph Structures for model training—0
A Vector Space for Distributional Semantics for Entailment—0
DeSpin: a prototype system for detecting spin in biomedical publications—0
Detecting Backdoor Attacks via Similarity in Semantic Communication Systems—0
Detecting Collocations Similarity via Logical-Linguistic Model—0
Detecting Paraphrases of Standard Clause Titles in Insurance Contracts—0
Detecting Redundant Health Survey Questions Using Language-agnostic BERT Sentence Embedding (LaBSE)—0
Cross-Lingual Syntactically Informed Distributed Word Representations—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