activity
20242026
most citedEagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligence

NVIDIA, :, Amala Sanjay Deshmukh +204

We introduce Nemotron 3 Nano Omni, the latest model in the Nemotron multimodal series and the first to natively support audio inputs alongside text, images, and video. Nemotron 3 N…

cs.CL2025

Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

NVIDIA, :, Aaron Blakeman +198

As inference-time scaling becomes critical for enhanced reasoning capabilities, it is increasingly becoming important to build models that are efficient to infer. We introduce Nemo…

cs.CV2025★ 2 cited

Éclair -- Extracting Content and Layout with Integrated Reading Order for Documents

Ilia Karmanov, Amala Sanjay Deshmukh, Lukas Voegtle +8

Optical Character Recognition (OCR) technology is widely used to extract text from images of documents, facilitating efficient digitization and data retrieval. However, merely extr…

cs.CV2025★ 2 cited

Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models

Zhiqi Li, Guo Chen, Shilong Liu +24

Recently, promising progress has been made by open-source vision-language models (VLMs) in bringing their capabilities closer to those of proprietary frontier models. However, most…

cs.CV2024

Temporal Lidar Depth Completion

Pietari Kaskela, Philipp Fischer, Timo Roman

Given the lidar measurements from an autonomous vehicle, we can project the points and generate a sparse depth image. Depth completion aims at increasing the resolution of such a d…