most citedERNIE 5.0 Technical Report

2 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AI2026

QCFuse: Query-Aware Cache Fusion via Compressed View for Efficient RAG Serving

Jianxin Yan, Wangze Ni, Zhenxin Li +8

Retrieval-augmented generation (RAG) improves large language model (LLM) answer quality by grounding generation in external evidence, but processing retrieved contexts makes the pr…

cs.LG2026

Hierarchical SVG Tokenization: Learning Compact Visual Programs for Scalable Vector Graphics Modeling

Ximing Xing, Ziteng Xue, Zhenxi Li +8

Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, existing approaches still rely on…

cs.CL2026★ 2 cited

ERNIE 5.0 Technical Report

Haifeng Wang, Hua Wu, Tian Wu +432

In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…

cs.CV2025

JarvisEvo: Towards a Self-Evolving Photo Editing Agent with Synergistic Editor-Evaluator Optimization

Yunlong Lin, Linqing Wang, Kunjie Lin +11

Agent-based editing models have substantially advanced interactive experiences, processing quality, and creative flexibility. However, two critical challenges persist: (1) instruct…

cs.CL2025

EFPC: Towards Efficient and Flexible Prompt Compression

Yun-Hao Cao, Yangsong Wang, Shuzheng Hao +4

The emergence of large language models (LLMs) like GPT-4 has revolutionized natural language processing (NLP), enabling diverse, complex tasks. However, extensive token counts lead…

cs.CV2025

PVChat: Personalized Video Chat with One-Shot Learning

Yufei Shi, Weilong Yan, Gang Xu +6

Video large language models (ViLLMs) excel in general video understanding, e.g., recognizing activities like talking and eating, but struggle with identity-aware comprehension, suc…