Research author
Wei Chen
13 AI research papers in the One9Founders library, with summaries and links to original sources.
Papers by Wei Chen
VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning
Junxiang Xu, Ruisi Wang, Fanyi Pu, et al.
Contextual Information Policy Optimization for Search Agents
Xingyu Guo, Wei Chen, Linlin Yang, et al.
ArtAnno: Annotating Implicit Semantics in Artworks through LLM Agent-Driven Bidirectional Human-AI Augmentation
Xiaoyan Gu, Yifang Wang, Wenqing Zheng, et al.
Requirement--Evidence Alignment for Compositional E-Commerce Queries
Weihao Shen, Wei Chen, Fuwei Zhang, et al.
Unpaired Modality-Agnostic Generative Recommendation
Weihao Shen, Wei Chen, Fuwei Zhang, et al.
M$^3$Exam: Benchmarking Multimodal Memory for Realistic User-Agent Interactions
Zhengjun Huang, Wenxuan Liu, Zhoujin Tian, et al.
ViCrop-Det: Spatial Attention Entropy Guided Cropping for Training-Free Small-Object Detection
Hui Wang, Hongze Li, Wei Chen, et al.
Exploring the Capability Boundaries of LLMs in Mastering of Chinese Chouxiang Language
Dianqing Lin, Tian Lan, Jiali Zhu, et al.
MedRCube: A Multidimensional Framework for Fine-Grained and In-Depth Evaluation of MLLMs in Medical Imaging
Zhijie Bao, Fangke Chen, Licheng Bao, et al.
DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding
Hao Yan, Yuliang Liu, Xingchen Liu, et al.
Data, Not Model: Explaining Bias toward LLM Texts in Neural Retrievers
Wei Huang, Keping Bi, Yinqiong Cai, et al.
Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement
Qimin Zhong, Hao Liao, Haiming Qin, et al.
SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits
Edward Lin, Sahil Modi, Siva Kumar Sastry Hari, et al.
SOL-ExecBench is a new benchmark for evaluating AI systems that optimize GPU kernels by measuring how close they get to the theoretical maximum performance (Speed-of-Light) that the hardware can achieve, rather than just comparing against other software implementations. It includes 235 real optimization problems from actual AI models and uses a special pipeline called SOLAR to calculate what perfect performance would look like for each kernel. The benchmark includes safeguards to prevent cheating and focuses on modern NVIDIA Blackwell GPUs with various precision formats.