289 citations · 337 across the 13 of their papers we have counts for
14 papers
Mellum2 Technical Report
Marko Kojic, Ivan Bondyrev, Aral de Moor +6
We present Mellum 2, an open-weight 12B-parameter Mixture-of-Experts (MoE) language model with 2.5B active parameters per token. Mellum 2 is a general-purpose language model specia…
Mellum: Production-Grade in-IDE Contextual Code Completion with Multi-File Project Understanding
Nikita Pavlichenko, Iurii Nazarov, Ivan Dolgov +10
We present the Mellum models family, open-weight code completion models designed for interactive use in JetBrains IDEs. Mellums have 4B parameters, adopt a Llama-style architecture…
Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence
Granite Vision Team, Leonid Karlinsky, Assaf Arbelle +60
We introduce Granite Vision, a lightweight large language model with vision capabilities, specifically designed to excel in enterprise use cases, particularly in visual document un…
Augmenting In-Context-Learning in LLMs via Automatic Data Labeling and Refinement
Joseph Shtok, Amit Alfassy, Foad Abo Dahood +3
It has been shown that Large Language Models' (LLMs) performance can be improved for many tasks using Chain of Thought (CoT) or In-Context Learning (ICL), which involve demonstrati…
NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning
Eli Schwartz, Leshem Choshen, Joseph Shtok +3
Language models struggle with handling numerical data and performing arithmetic operations. We hypothesize that this limitation can be partially attributed to non-intuitive textual…
CHARTER: heatmap-based multi-type chart data extraction
Joseph Shtok, Sivan Harary, Ophir Azulai +3
The digital conversion of information stored in documents is a great source of knowledge. In contrast to the documents text, the conversion of the embedded documents graphics, such…
Detector-Free Weakly Supervised Grounding by Separation
Assaf Arbelle, Sivan Doveh, Amit Alfassy +14
Nowadays, there is an abundance of data involving images and surrounding free-form text weakly corresponding to those images. Weakly Supervised phrase-Grounding (WSG) deals with th…
StarNet: towards Weakly Supervised Few-Shot Object Detection
Leonid Karlinsky, Joseph Shtok, Amit Alfassy +8
Few-shot detection and classification have advanced significantly in recent years. Yet, detection approaches require strong annotation (bounding boxes) both for pre-training and fo…
LaSO: Label-Set Operations networks for multi-label few-shot learning
Amit Alfassy, Leonid Karlinsky, Amit Aides +5
Example synthesis is one of the leading methods to tackle the problem of few-shot learning, where only a small number of samples per class are available. However, current synthesis…
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Eli Schwartz, Leonid Karlinsky, Joseph Shtok +6
Learning to classify new categories based on just one or a few examples is a long-standing challenge in modern computer vision. In this work, we proposes a simple yet effective met…
RepMet: Representative-based metric learning for classification and one-shot object detection
Leonid Karlinsky, Joseph Shtok, Sivan Harary +5
Distance metric learning (DML) has been successfully applied to object classification, both in the standard regime of rich training data and in the few-shot scenario, where each ca…
Spatially-Adaptive Reconstruction in Computed Tomography using Neural Networks
Joseph Shtok, Michael Zibulevsky, Michael Elad
We propose a supervised machine learning approach for boosting existing signal and image recovery methods and demonstrate its efficacy on example of image reconstruction in compute…
Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning
Joseph Shtok, Michael Zibulevsky, Michael Elad
We propose a direct reconstruction algorithm for Computed Tomography, based on a local fusion of a few preliminary image estimates by means of a non-linear fusion rule. One such ru…
Analysis of Basis Pursuit Via Capacity Sets
Joseph Shtok, Michael Elad
Finding the sparsest solution for an under-determined linear system of equations is of interest in many applications. This problem is known to be NP-hard. Recent work st…