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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 341–350 of 1564 papers

Title	Date	Tasks	Status	Hype
A Collection of Pragmatic-Similarity Judgments over Spoken Dialog Utterances	Mar 21, 2024	Machine TranslationSemantic Similarity	CodeCode Available	0
RAmBLA: A Framework for Evaluating the Reliability of LLMs as Assistants in the Biomedical Domain	Mar 21, 2024	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Beyond Surface Similarity: Detecting Subtle Semantic Shifts in Financial Narratives	Mar 21, 2024	Decision MakingSemantic Similarity	—Unverified	0
A Modified Word Saliency-Based Adversarial Attack on Text Classification Models	Mar 17, 2024	Adversarial AttackClassification	—Unverified	0
NLP Verification: Towards a General Methodology for Certifying Robustness	Mar 15, 2024	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
SIFiD: Reassess Summary Factual Inconsistency Detection with LLM	Mar 12, 2024	Natural Language InferenceSemantic Similarity	—Unverified	0
Knowledge-aware Alert Aggregation in Large-scale Cloud Systems: a Hybrid Approach	Mar 11, 2024	CoLALanguage Modelling	—Unverified	0
Deep Contrastive Multi-view Clustering under Semantic Feature Guidance	Mar 9, 2024	ClusteringContrastive Learning	—Unverified	0
Is Cosine-Similarity of Embeddings Really About Similarity?	Mar 8, 2024	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval	Mar 8, 2024	Cross-Modal RetrievalCross-modal retrieval with noisy correspondence	CodeCode Available	1

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All datasets Annotated corpus for semantic similarity of clinical trial outcomes (expanded corpus)Annotated corpus for semantic similarity of clinical trial outcomes (original corpus)SICK BIOSSES CHIP-STS ClinicalSTS MedSTS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	93.38	—	Unverified
2	SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	91.51	—	Unverified
3	SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	90.69	—	Unverified
4	BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	89.16	—	Unverified
5	BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	89.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.75	—	Unverified
2	SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.3	—	Unverified
3	SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.3	—	Unverified
4	BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	86.8	—	Unverified
5	BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	84.21	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Doc2VecC	MSE	0.31	—	Unverified
2	LSTM (Tai et al., 2015)	MSE	0.28	—	Unverified
3	Bidirectional LSTM (Tai et al., 2015)	MSE	0.27	—	Unverified
4	combine-skip (Kiros et al., 2015)	MSE	0.27	—	Unverified
5	Dependency Tree-LSTM (Tai et al., 2015)	MSE	0.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BioLinkBERT (large)	Pearson Correlation	0.94	—	Unverified
2	BioLinkBERT (base)	Pearson Correlation	0.93	—	Unverified
3	NCBI_BERT(base) (P+M)	Pearson Correlation	0.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MacBERT-large	Macro F1	85.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CharacterBERT (base, medical, ensemble)	Pearson Correlation	85.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	NCBI_BERT(base) (P+M)	Pearson Correlation	0.85	—	Unverified