2 citations · 2 across the 7 of their papers we have counts for
8 papers
Brain-CLIPLM: Semantic Compression for EEG-to-Text Decoding
Xiaoli Yang, Huiyuan Tian, Yurui Li +3
Decoding natural language from non-invasive electroencephalography (EEG) remains constrained by low signal-to-noise ratio and limited information bandwidth. This raises a central q…
FairJudge: An Adaptive, Debiased, and Consistent LLM-as-a-Judge
Bo Yang, Lanfei Feng, Yunkui Chen +3
Existing LLM-as-a-Judge systems suffer from three fundamental limitations: limited adaptivity to task- and domain-specific evaluation criteria, systematic biases driven by non-sema…
ZPD Detector: Data Selection via Capability-Difficulty Alignment for Large Language Models
Bo Yang, Yunkui Chen, Lanfei Feng +2
As the cost of training large language models continues to increase and high-quality training data become increasingly scarce, selecting high-value samples or synthesizing effectiv…
AgriAgent: Contract-Driven Planning and Capability-Aware Tool Orchestration in Real-World Agriculture
Bo Yang, Yu Zhang, Yunkui Chen +4
Intelligent agent systems in real-world agricultural scenarios must handle diverse tasks under multimodal inputs, ranging from lightweight information understanding to complex mult…
AgriGPT-Omni: A Unified Speech-Vision-Text Framework for Multilingual Agricultural Intelligence
Bo Yang, Lanfei Feng, Yunkui Chen +5
Despite rapid advances in multimodal large language models, agricultural applications remain constrained by the lack of multilingual speech data, unified multimodal architectures,…
AgriGPT-VL: Agricultural Vision-Language Understanding Suite
Bo Yang, Yunkui Chen, Lanfei Feng +8
Despite rapid advances in multimodal large language models, agricultural applications remain constrained by the scarcity of domain-tailored models, curated vision-language corpora,…
AgriGPT: a Large Language Model Ecosystem for Agriculture
Bo Yang, Yu Zhang, Lanfei Feng +10
Despite the rapid progress of Large Language Models (LLMs), their application in agriculture remains limited due to the lack of domain-specific models, curated datasets, and robust…
Incorporating Feature Pyramid Tokenization and Open Vocabulary Semantic Segmentation
Jianyu Zhang, Li Zhang, Shijian Li
The visual understanding are often approached from 3 granular levels: image, patch and pixel. Visual Tokenization, trained by self-supervised reconstructive learning, compresses vi…