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Research & Development
ReclAIm: An Autonomous Framework for Sustaining Medical Imaging AI Performance
TLDR: ReclAIm is a novel multi-agent framework designed to autonomously monitor, evaluate, and fine-tune medical image classification models. Built on a large language model...
Research & Development
Unlocking Extreme Long-Context Understanding in Language Models
TLDR: This research paper investigates chunk-based sparse attention models to enable language models to process extremely long texts efficiently. It identifies three critical architectural...
Research & Development
Optimizing Vision-Language Models: A New Approach to Visual Token Pruning
TLDR: ZSPAPrune is a novel, zero-shot method for efficiently pruning visual tokens in Vision-Language Models (VLMs). Unlike previous methods, it considers the text prompt...
Research & Development
AI’s Eye on Bangladesh: Mapping River Erosion and Lost Villages with Satellite Imagery
TLDR: A new research paper introduces a deep learning framework using a fine-tuned Segment Anything Model (SAM) to detect and quantify riverbank erosion in...
Research & Development
FineVision: A Unified Data Resource for Vision-Language Models
TLDR: FineVision is a new, large-scale, and meticulously curated open dataset of 24 million samples for training vision-language models (VLMs). It unifies over 200...
Research & Development
Nyx: Advancing Retrieval-Augmented Generation for Mixed-Modal Information
TLDR: A new research paper introduces Nyx, a unified mixed-modal retriever designed for Universal Retrieval-Augmented Generation (URAG). URAG aims to improve vision-language generation by...