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20232026
most citedExploring the Naturalness of AI-Generated Images

9 citations · 29 across the 33 of their papers we have counts for

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7 papers · 1 filter

cs.AI2026

SciMIF: Understanding Multimodal Instruction Following in Scientific Domains

Ye Shen, Yuting Zheng, Dun Pei +4

Understanding instruction-following capabilities in scientific domains is essential for effectively leveraging Multimodal Large Language Models (MLLMs) to advance the development o…

cs.CV2026

GeoR-Bench: Evaluating Geoscience Visual Reasoning

Yushuo Zheng, Zicheng Zhang, Huiyu Duan +7

Geoscience intelligence is expected to understand, reason about, and predict earth system changes to support human decision-making in critical domains such as disaster response, cl…

cs.LG2026

SafeSci: Safety Evaluation of Large Language Models in Science Domains and Beyond

Xiangyang Zhu, Yuan Tian, Qi Jia +14

The success of large language models (LLMs) in scientific domains has heightened safety concerns, prompting numerous benchmarks to evaluate their scientific safety. Existing benchm…

cs.CV2026

A: Towards Advertising Aesthetic Assessment

Kaiyuan Ji, Yixuan Gao, Lu Sun +7

Advertising images significantly impact commercial conversion rates and brand equity, yet current evaluation methods rely on subjective judgments, lacking scalability, standardized…

cs.CL2026

UniDial-EvalKit: A Unified Toolkit for Evaluating Multi-Faceted Conversational Abilities

Qi Jia, Haodong Zhao, Dun Pei +7

Benchmarking large language models (LLMs) and agents in multi-turn interactive scenarios is essential for understanding their practical capabilities. However, existing evaluation p…

cs.AI2026

STAR : Bridging Statistical and Agentic Reasoning for Large Model Performance Prediction

Xiaoxiao Wang, Chunxiao Li, Junying Wang +6

As comprehensive large model evaluation becomes prohibitively expensive, predicting model performance from limited observations has become essential. However, existing statistical…

cs.CV2026

KidVis: Do Multimodal Large Language Models Possess the Visual Perceptual Capabilities of a 6-Year-Old?

Xianfeng Wang, Kaiwei Zhang, Qi Jia +3

While Multimodal Large Language Models (MLLMs) have demonstrated impressive proficiency in high-level reasoning tasks, such as complex diagrammatic interpretation, it remains an op…