most citedERNIE 5.0 Technical Report

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL20262 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

Reasoning Palette: Modulating Reasoning via Latent Contextualization for Controllable Exploration for (V)LMs

Rujiao Long, Yang Li, Xingyao Zhang +7

Exploration capacity shapes both inference-time performance and reinforcement learning (RL) training for large (vision-) language models, as stochastic sampling often yields redund…

cs.AI20251 cited

Beyond Training: Enabling Self-Evolution of Agents with MOBIMEM

Zibin Liu, Cheng Zhang, Xi Zhao +6

Large Language Model (LLM) agents are increasingly deployed to automate complex workflows in mobile and desktop environments. However, current model-centric agent architectures str…

cs.AI2025

RAVR: Reference-Answer-guided Variational Reasoning for Large Language Models

Tianqianjin Lin, Xi Zhao, Xingyao Zhang +5

Reinforcement learning (RL) can refine the reasoning abilities of large language models (LLMs), but critically depends on a key prerequisite: the LLM can already generate high-util…

cs.MA2025

MobiAgent: A Systematic Framework for Customizable Mobile Agents

Cheng Zhang, Erhu Feng, Xi Zhao +7

With the rapid advancement of Vision-Language Models (VLMs), GUI-based mobile agents have emerged as a key development direction for intelligent mobile systems. However, existing a…