most citedThe Amazon Nova Family of Models: Technical Report and Model Card

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Diffusion Precipitation Generation with Medium-range Weather Forecasting

Guowen Li, Yang Liu, Mengxuan Chen +11

Accurate daily precipitation forecasts are important for weather-sensitive decisions. Although recent Weather Foundation Models (WFMs) have achieved significant progress, they are…

cs.CV2026

V-Loop: Visual Logical Loop Verification for Hallucination Detection in Medical Visual Question Answering

Mengyuan Jin, Zehui Liao, Yong Xia

Multimodal Large Language Models (MLLMs) have shown remarkable capability in assisting disease diagnosis in medical visual question answering (VQA). However, their outputs remain v…

cs.LG2025

Task-Adaptive Parameter-Efficient Fine-Tuning for Weather Foundation Models

Shilei Cao, Hehai Lin, Jiashun Cheng +9

While recent advances in machine learning have equipped Weather Foundation Models (WFMs) with substantial generalization capabilities across diverse downstream tasks, the escalatin…

cs.AI2025★ 2 cited

The Amazon Nova Family of Models: Technical Report and Model Card

Amazon AGI, Aaron Langford, Aayush Shah +783

We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…

cs.LG2025★ 1 cited

TianQuan-S2S: A Subseasonal-to-Seasonal Global Weather Model via Incorporate Climatology State

Guowen Li, Xintong Liu, Yang Liu +11

Accurate Subseasonal-to-Seasonal (S2S) forecasting is vital for decision-making in agriculture, energy production, and emergency management. However, it remains a challenging and u…