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 901–925 of 1564 papers

TitleStatusHype
Cluster Analysis with Deep Embeddings and Contrastive Learning—0
Sorting through the noise: Testing robustness of information processing in pre-trained language models—0
Rethinking Crowd Sourcing for Semantic Similarity—0
Towards Universal Dense Retrieval for Open-domain Question Answering—0
Investigating Entropy for Extractive Document Summarization—0
ConvFiT: Conversational Fine-Tuning of Pretrained Language Models—0
Adversarial Training with Contrastive Learning in NLP—0
Contrastive Word Embedding Learning for Neural Machine Translation—0
Transformers Can Compose Skills To Solve Novel Problems Without Finetuning—0
A Semantic Indexing Structure for Image Retrieval—0
Data Driven Content Creation using Statistical and Natural Language Processing Techniques for Financial Domain—0
On Length Divergence Bias in Textual Matching Models—0
PR-Net: Preference Reasoning for Personalized Video Highlight Detection—0
Paragraph Similarity Matches for Generating Multiple-choice Test Items—0
Assessing the Eligibility of Backtranslated Samples Based on Semantic Similarity for the Paraphrase Identification Task—0
Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification—0
Multiplex Graph Neural Network for Extractive Text Summarization—0
Lingxi: A Diversity-aware Chinese Modern Poetry Generation System—0
Multi-Attributed and Structured Text-to-Face Synthesis—0
Czech News Dataset for Semantic Textual Similarity—0
Reinforce Attack: Adversarial Attack against BERT with Reinforcement Learning—0
Semantic Answer Similarity for Evaluating Question Answering Models—0
Semantic Similarity Based Evaluation for Abstractive News SummarizationCode0
Text-in-Context: Token-Level Error Detection for Table-to-Text GenerationCode0
Explanations for CommonsenseQA: New Dataset and 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 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