Semantic Textual Similarity
564 papers with code • 13 benchmarks • 17 datasets
Semantic textual similarity deals with determining how similar two pieces of texts are. This can take the form of assigning a score from 1 to 5. Related tasks are paraphrase or duplicate identification.
Image source: Learning Semantic Textual Similarity from Conversations
Benchmarks
These leaderboards are used to track progress in Semantic Textual Similarity
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Libraries
Use these libraries to find Semantic Textual Similarity models and implementations
GLUE
MRPC
SICK
SentEval
CARER
MTEB
STS Benchmark
EVALution
Latest papers
Contrastive Learning in Distilled Models
kennethlimjf/contrastive-learning-in-distilled-models
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Natural Language Processing models like BERT can provide state-of-the-art word embeddings for downstream NLP tasks.
Noise Contrastive Estimation-based Matching Framework for Low-Resource Security Attack Pattern Recognition
Tactics, Techniques and Procedures (TTPs) represent sophisticated attack patterns in the cybersecurity domain, described encyclopedically in textual knowledge bases.
A character-based steganography using masked language modeling
emirozturk/MLMStego
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IEEE Access 2024
In this study, a steganography method based on BERT transformer model is proposed for hiding text data in cover text.
Do Vision and Language Encoders Represent the World Similarly?
In the absence of statistical similarity in aligned encoders like CLIP, we show that a possible matching of unaligned encoders exists without any training.
PeFoMed: Parameter Efficient Fine-tuning of Multimodal Large Language Models for Medical Imaging
In this paper, we propose a parameter efficient framework for fine-tuning MLLMs, specifically validated on medical visual question answering (Med-VQA) and medical report generation (MRG) tasks, using public benchmark datasets.
Unsupervised hard Negative Augmentation for contrastive learning
claudiashu/una
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We present Unsupervised hard Negative Augmentation (UNA), a method that generates synthetic negative instances based on the term frequency-inverse document frequency (TF-IDF) retrieval model.
Are we describing the same sound? An analysis of word embedding spaces of expressive piano performance
Using a music research dataset of free text performance characterizations and a follow-up study sorting the annotations into clusters, we derive a ground truth for a domain-specific semantic similarity structure.
Def2Vec: Extensible Word Embeddings from Dictionary Definitions
Def2Vec introduces a novel paradigm for word embeddings, leveraging dictionary definitions to learn semantic representations.
Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models
Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature.
Explicitly Integrating Judgment Prediction with Legal Document Retrieval: A Law-Guided Generative Approach
e-qin/gear
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Legal document retrieval and judgment prediction are crucial tasks in intelligent legal systems.
