5 citations · 6 across the 15 of their papers we have counts for
5 papers · 1 filter
OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs
Caorui Li, Yu Chen, Yiyan Ji +40
Recent advances in multimodal large language models (MLLMs) have demonstrated substantial potential in video understanding. However, existing benchmarks fail to comprehensively eva…
Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding
StepFun, :, Bin Wang +195
Large language models (LLMs) face low hardware efficiency during decoding, especially for long-context reasoning tasks. This paper introduces Step-3, a 321B-parameter VLM with hard…
Predictable Scale: Part II, Farseer: A Refined Scaling Law in Large Language Models
Houyi Li, Wenzhen Zheng, Qiufeng Wang +8
Training Large Language Models (LLMs) is prohibitively expensive, creating a critical scaling gap where insights from small-scale experiments often fail to transfer to resource-int…
Is Compression Really Linear with Code Intelligence?
Shijie Xuyang, Xianzhen Luo, Zheng Chu +6
Understanding the relationship between data compression and the capabilities of Large Language Models (LLMs) is crucial, especially in specialized domains like code intelligence. P…
Predictable Scale: Part I, Step Law -- Optimal Hyperparameter Scaling Law in Large Language Model Pretraining
Houyi Li, Wenzhen Zheng, Qiufeng Wang +10
The impressive capabilities of Large Language Models (LLMs) across diverse tasks are now well established, yet their effective deployment necessitates careful hyperparameter optimi…