Visualization of semantic similarities in word embeddings.
We propose a novel modular framework that learns to dynamically mix low-rank adapters (LoRAs) to improve visual analogy learning, enabling flexible and generalizable image edits based on example transformations.
A methodology to harness the power of analogies, making them work for you
Classification and solving of morphological analogies with neural models
An omnilingual model to solve monolingual and bilingual analogies
word2vec app: word vector functions
Analogy solver using Google's pretrained word vectors
This project is to evaluate the effectiveness of two advanced NLP models—SBERT (Sentence-BERT) and MiniLM—in classifying analogies using the FrameNet dataset. Analogies are fundamental in human cognition and reasoning, helping us understand relationships between concepts and make inferences.
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