4 citations · 17 across the 10 of their papers we have counts for
10 papers
Gemma 4 Technical Report
Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320
We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemm…
Analyzing the Efficacy of an LLM-Only Approach for Image-based Document Question Answering
Nidhi Hegde, Sujoy Paul, Gagan Madan +1
Recent document question answering models consist of two key components: the vision encoder, which captures layout and visual elements in images, and a Large Language Model (LLM) t…
Is it an i or an l: Test-time Adaptation of Text Line Recognition Models
Debapriya Tula, Sujoy Paul, Gagan Madan +3
Recognizing text lines from images is a challenging problem, especially for handwritten documents due to large variations in writing styles. While text line recognition models are…
Weakly supervised information extraction from inscrutable handwritten document images
Sujoy Paul, Gagan Madan, Akankshya Mishra +3
State-of-the-art information extraction methods are limited by OCR errors. They work well for printed text in form-like documents, but unstructured, handwritten documents still rem…
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision
Lucas Beyer, Bo Wan, Gagan Madan +9
There has been a recent explosion of computer vision models which perform many tasks and are composed of an image encoder (usually a ViT) and an autoregressive decoder (usually a T…
Sample-Efficient Personalization: Modeling User Parameters as Low Rank Plus Sparse Components
Soumyabrata Pal, Prateek Varshney, Prateek Jain +5
Personalization of machine learning (ML) predictions for individual users/domains/enterprises is critical for practical recommendation systems. Standard personalization approaches…
Node-Level Differentially Private Graph Neural Networks
Ameya Daigavane, Gagan Madan, Aditya Sinha +3
Graph Neural Networks (GNNs) are a popular technique for modelling graph-structured data and computing node-level representations via aggregation of information from the neighborho…
Block-Value Symmetries in Probabilistic Graphical Models
Gagan Madan, Ankit Anand, Mausam +1
One popular way for lifted inference in probabilistic graphical models is to first merge symmetric states into a single cluster (orbit) and then use these for downstream inference,…
A Survey of Distant Supervision Methods using PGMs
Gagan Madan
Relation Extraction refers to the task of populating a database with tuples of the form , where is a relation and , are entities. Distant supervision is…
Topic Modeling Using Distributed Word Embeddings
Ramandeep S Randhawa, Parag Jain, Gagan Madan
We propose a new algorithm for topic modeling, Vec2Topic, that identifies the main topics in a corpus using semantic information captured via high-dimensional distributed word embe…