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 301–350 of 1564 papers

TitleStatusHype
SentenceKV: Efficient LLM Inference via Sentence-Level Semantic KV Caching—0
Beyond Detection: Designing AI-Resilient Assessments with Automated Feedback Tool to Foster Critical Thinking—0
Discovering Knowledge Deficiencies of Language Models on Massive Knowledge Base—0
HyperFree: A Channel-adaptive and Tuning-free Foundation Model for Hyperspectral Remote Sensing Imagery—0
A Quantitative Approach to Evaluating Open-Source EHR Systems for Indian Healthcare—0
BeLightRec: A lightweight recommender system enhanced with BERT—0
Ontology-based Semantic Similarity Measures for Clustering Medical Concepts in Drug SafetyCode0
SeLIP: Similarity Enhanced Contrastive Language Image Pretraining for Multi-modal Head MRI—0
CausalRAG: Integrating Causal Graphs into Retrieval-Augmented Generation—0
Unleashing the power of text for credit default prediction: Comparing human-written and generative AI-refined texts—0
Vision Transformer Based Semantic Communications for Next Generation Wireless Networks—0
KVShare: An LLM Service System with Efficient and Effective Multi-Tenant KV Cache Reuse—0
A General Close-loop Predictive Coding Framework for Auditory Working Memory—0
TLAC: Two-stage LMM Augmented CLIP for Zero-Shot ClassificationCode0
Measuring Similarity in Causal Graphs: A Framework for Semantic and Structural Analysis—0
PromptMap: An Alternative Interaction Style for AI-Based Image GenerationCode0
AuthorMist: Evading AI Text Detectors with Reinforcement Learning—0
Asymmetric Visual Semantic Embedding Framework for Efficient Vision-Language AlignmentCode0
MIGA: Mutual Information-Guided Attack on Denoising Models for Semantic Manipulation—0
Are We Truly Forgetting? A Critical Re-examination of Machine Unlearning Evaluation Protocols—0
SEED: Towards More Accurate Semantic Evaluation for Visual Brain Decoding—0
Improving RAG Retrieval via Propositional Content Extraction: a Speech Act Theory Approach—0
Token-Level Privacy in Large Language Models—0
SEOE: A Scalable and Reliable Semantic Evaluation Framework for Open Domain Event Detection—0
Label Ranker: Self-Aware Preference for Classification Label Position in Visual Masked Self-Supervised Pre-Trained ModelCode0
Language-agnostic, automated assessment of listeners' speech recall using large language models—0
Statistical Mechanics of Semantic Compression—0
TempRetriever: Fusion-based Temporal Dense Passage Retrieval for Time-Sensitive Questions—0
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models—0
How Vital is the Jurisprudential Relevance: Law Article Intervened Legal Case Retrieval and Matching—0
EnDive: A Cross-Dialect Benchmark for Fairness and Performance in Large Language Models—0
Uncertainty Quantification of Large Language Models through Multi-Dimensional Responses—0
ATEB: Evaluating and Improving Advanced NLP Tasks for Text Embedding Models—0
CLIMB-3D: Continual Learning for Imbalanced 3D Instance SegmentationCode0
Constructing a Norm for Children's Scientific Drawing: Distribution Features Based on Semantic Similarity of Large Language Models—0
Exploring RWKV for Sentence Embeddings: Layer-wise Analysis and Baseline Comparison for Semantic SimilarityCode0
Evolutionary Algorithms Approach For Search Based On Semantic Document Similarity—0
DeepRTL: Bridging Verilog Understanding and Generation with a Unified Representation Model—0
A Meta-Evaluation of Style and Attribute Transfer Metrics—0
Breaking the Clusters: Uniformity-Optimization for Text-Based Sequential RecommendationCode0
Event Segmentation Applications in Large Language Model Enabled Automated Recall Assessments—0
HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation—0
Balanced Multi-Factor In-Context Learning for Multilingual Large Language Models—0
Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal ReasoningCode0
Bridging LLM-Generated Code and Requirements: Reverse Generation technique and SBC Metric for Developer InsightsCode0
PDV: Prompt Directional Vectors for Zero-shot Composed Image Retrieval—0
Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering—0
Enhancing Health Information Retrieval with RAG by Prioritizing Topical Relevance and Factual Accuracy—0
How does a Multilingual LM Handle Multiple Languages?—0
Detecting Backdoor Attacks via Similarity in Semantic Communication Systems—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