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08/28/2023
Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond
Visual similarities discovery (VSD) is an important task with broad e-co...
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06/28/2023
Representation Learning via Variational Bayesian Networks
We present Variational Bayesian Network (VBN) - a novel Bayesian entity ...
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06/09/2023
GPT-Calls: Enhancing Call Segmentation and Tagging by Generating Synthetic Conversations via Large Language Models
Transcriptions of phone calls are of significant value across diverse fi...
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08/13/2022
Interpreting BERT-based Text Similarity via Activation and Saliency Maps
Recently, there has been growing interest in the ability of Transformer-...
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08/13/2022
MetricBERT: Text Representation Learning via Self-Supervised Triplet Training
We present MetricBERT, a BERT-based model that learns to embed text unde...
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04/23/2022
Grad-SAM: Explaining Transformers via Gradient Self-Attention Maps
Transformer-based language models significantly advanced the state-of-th...
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12/10/2021
Pre-training and Fine-tuning Transformers for fMRI Prediction Tasks
We present the TFF Transformer framework for the analysis of functional ...
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09/22/2021
Caption Enriched Samples for Improving Hateful Memes Detection
The recently introduced hateful meme challenge demonstrates the difficul...
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09/02/2021
GAM: Explainable Visual Similarity and Classification via Gradient Activation Maps
We present Gradient Activation Maps (GAM) - a machinery for explaining p...
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06/02/2021
Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference
We present a novel model for the problem of ranking a collection of docu...
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04/05/2021
Adaptive Gradient Balancing for UndersampledMRI Reconstruction and Image-to-Image Translation
Recent accelerated MRI reconstruction models have used Deep Neural Netwo...
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09/25/2020
RecoBERT: A Catalog Language Model for Text-Based Recommendations
Language models that utilize extensive self-supervised pre-training from...
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06/25/2020
MTAdam: Automatic Balancing of Multiple Training Loss Terms
When training neural models, it is common to combine multiple loss terms...
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11/26/2019
Spectra2pix: Generating Nanostructure Images from Spectra
The design of the nanostructures that are used in the field of nano-phot...
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11/05/2019
MML: Maximal Multiverse Learning for Robust Fine-Tuning of Language Models
Recent state-of-the-art language models utilize a two-phase training pro...
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08/14/2019
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding
Attention based models have become the new state-of-the-art in natural l...
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05/02/2019
