most citedERNIE 5.0 Technical Report

2 citations · 3 across the 7 of their papers we have counts for

collaborators

8 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.AI2026

SafeGround: Know When to Trust GUI Grounding Models via Uncertainty Calibration

Qingni Wang, Yue Fan, Xin Eric Wang

Graphical User Interface (GUI) grounding aims to translate natural language instructions into executable screen coordinates, enabling automated GUI interaction. Nevertheless, incor…

cs.AI2026

Cross-Modal Memory Compression for Efficient Multi-Agent Debate

Jing Wu, Yue Sun, Tianpei Xie +7

Multi-agent debate can improve reasoning quality and reduce hallucinations, but it incurs rapidly growing context as debate rounds and agent count increase. Retaining full textual…

cs.CV2026

ShowUI-Aloha: Human-Taught GUI Agent

Yichun Zhang, Xiangwu Guo, Yauhong Goh +5

Graphical User Interfaces (GUIs) are central to human-computer interaction, yet automating complex GUI tasks remains a major challenge for autonomous agents, largely due to a lack…

cs.CL2026

PALM-Bench: A Comprehensive Benchmark for Personalized Audio-Language Models

Yuwen Wang, Xinyuan Qian, Tian-Hao Zhang +6

Large Audio-Language Models (LALMs) have demonstrated strong performance in audio understanding and generation. Yet, our extensive benchmarking reveals that their behavior is large…

cs.AI2025

PerPilot: Personalizing VLM-based Mobile Agents via Memory and Exploration

Xin Wang, Zhiyao Cui, Hao Li +10

Vision language model (VLM)-based mobile agents show great potential for assisting users in performing instruction-driven tasks. However, these agents typically struggle with perso…