activity
20242026
most citedNVILA: Efficient Frontier Visual Language Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

13 papers

cs.CV2026

From Visual Widgets to UI Code: Efficient Tool-Grounded Generation

Houston H. Zhang, Tao Zhang, Li Gu +5

Existing screenshot-to-code systems face a trade-off between flexibility and controllability. Direct multimodal generation can hallucinate visible details, whereas structured pipel…

cs.DC2026

Prism: Cost-Efficient Multi-LLM Serving via GPU Memory Ballooning

Shan Yu, Yifan Qiao, Mingyuan Ma +18

Inference providers must maintain availability for many LLMs, including low-volume but essential models, making resource efficiency increasingly important as token prices fall. Ana…

cs.CV20261 cited

NVILA: Efficient Frontier Visual Language Models

Zhijian Liu, Ligeng Zhu, Baifeng Shi +24

Visual language models (VLMs) have made significant advances in accuracy in recent years. However, their efficiency has received much less attention. This paper introduces NVILA, a…

cs.AI2026

K-Search: LLM Kernel Generation via Co-Evolving Intrinsic World Model

Shiyi Cao, Ziming Mao, Joseph E. Gonzalez +1

Optimizing GPU kernels is critical for efficient modern machine learning systems yet remains challenging due to the complex interplay of design factors and rapid hardware evolution…

cs.AI2025

SkyRL-Agent: Efficient RL Training for Multi-turn LLM Agent

Shiyi Cao, Dacheng Li, Fangzhou Zhao +12

We introduce SkyRL-Agent, a framework for efficient, multi-turn, long-horizon agent training and evaluation. It provides efficient asynchronous dispatching, lightweight tool integr…

cs.LG2025

Optimizing LLM Queries in Relational Data Analytics Workloads

Shu Liu, Asim Biswal, Amog Kamsetty +8

Batch data analytics is a growing application for Large Language Models (LLMs). LLMs enable users to perform a wide range of natural language tasks, such as classification, entity…