most citedERNIE 5.0 Technical Report

2 citations · 2 across the 8 of their papers we have counts for

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cs.CL2026

Beyond Global Scalars: Synergizing Token-Level Statistics and Deep Semantics for Adversarial AIGC Text Detection

Peiming Li, Yifan Wang, Zhiyuan Hu +3

The rapid evolution of large language models necessitates robust machine-generated text detection. Existing paradigms typically follow two isolated tracks. Training-free methods re…

cs.CL2026

HMS-BERT: Hybrid Multi-Task Self-Training for Multilingual and Multi-Label Cyberbullying Detection

Zixin Feng, Xinying Cui, Yifan Sun +5

Cyberbullying on social media is inherently multilingual and multi-faceted, where abusive behaviors often overlap across multiple categories. Existing methods are commonly limited…

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.CL2026

Yunque DeepResearch Technical Report

Yuxuan Cai, Xinyi Lai, Peng Yuan +8

Deep research has emerged as a transformative capability for autonomous agents, empowering Large Language Models to navigate complex, open-ended tasks. However, realizing its full…

cs.CL2026

Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning

Yifan Wang, Shiyu Li, Peiming Li +3

Chain-of-Thought (CoT) prompting has achieved remarkable success in unlocking the reasoning capabilities of Large Language Models (LLMs). Although CoT prompting enhances reasoning,…