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20242026
most citedVLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models

3 citations · 3 across the 12 of their papers we have counts for

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10 papers · 1 filter

cs.CL2026

OpenCompass: A Universal Evaluation Platform for Large Language Models

Maosong Cao, Kai Chen, Haodong Duan +27

In recent years, the field of artificial intelligence has undergone a paradigm shift from task-specific small-scale models to general-purpose large language models (LLMs). With the…

cs.CL2026

WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation

Shuangrui Ding, Xuanlang Dai, Long Xing +14

Large language and vision-language models increasingly power agents that act on a user's behalf through command-line interface (CLI) harnesses. However, most agent benchmarks still…

cs.CL2025

A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers

Ming Hu, Chenglong Ma, Wei Li +117

Scientific Large Language Models (Sci-LLMs) are transforming how knowledge is represented, integrated, and applied in scientific research, yet their progress is shaped by the compl…

cs.CL2025

NeedleBench: Evaluating LLM Retrieval and Reasoning Across Varying Information Densities

Mo Li, Songyang Zhang, Taolin Zhang +3

The capability of large language models to handle long-context information is crucial across various real-world applications. Existing evaluation methods often rely either on real-…

cs.CL2025

Redundancy Principles for MLLMs Benchmarks

Zicheng Zhang, Xiangyu Zhao, Xinyu Fang +6

With the rapid iteration of Multi-modality Large Language Models (MLLMs) and the evolving demands of the field, the number of benchmarks produced annually has surged into the hundr…

cs.CL2025

GDI-Bench: A Benchmark for General Document Intelligence with Vision and Reasoning Decoupling

Siqi Li, Yufan Shen, Xiangnan Chen +13

The rapid advancement of multimodal large language models (MLLMs) has profoundly impacted the document domain, creating a wide array of application scenarios. This progress highlig…