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20232026
most citedDense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models

2 citations · 5 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding

Jovana Kondic, Pengyuan Li, Dhiraj Joshi +24

Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a capability where current vision-language…

cs.CV2025★ 1 cited

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…

cs.CV2024★ 1 cited

ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs

Irene Huang, Wei Lin, M. Jehanzeb Mirza +11

Compositional Reasoning (CR) entails grasping the significance of attributes, relations, and word order. Recent Vision-Language Models (VLMs), comprising a visual encoder and a Lar…

cs.CV2023★ 1 cited

Learning Human Action Recognition Representations Without Real Humans

Howard Zhong, Samarth Mishra, Donghyun Kim +7

Pre-training on massive video datasets has become essential to achieve high action recognition performance on smaller downstream datasets. However, most large-scale video datasets…

cs.CV2023

LangNav: Language as a Perceptual Representation for Navigation

Bowen Pan, Rameswar Panda, SouYoung Jin +4

We explore the use of language as a perceptual representation for vision-and-language navigation (VLN), with a focus on low-data settings. Our approach uses off-the-shelf vision sy…