activity
20242026
most citedERNIE 5.0 Technical Report

2 citations · 2 across the 10 of their papers we have counts for

collaborators

12 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.CV2026

PhoStream: Benchmarking Real-World Streaming for Omnimodal Assistants in Mobile Scenarios

Xudong Lu, Huankang Guan, Yang Bo +10

Multimodal Large Language Models excel at offline audio-visual understanding, but their ability to serve as mobile assistants in continuous real-world streams remains underexplored…

cs.CV2026

JavisGPT: A Unified Multi-modal LLM for Sounding-Video Comprehension and Generation

Kai Liu, Jungang Li, Yuchong Sun +13

This paper presents JavisGPT, the first unified multimodal large language model (MLLM) for joint audio-video (JAV) comprehension and generation. JavisGPT has a concise encoder-LLM-…

cs.LG2025

FoldAct: Efficient and Stable Context Folding for Long-Horizon Search Agents

Jiaqi Shao, Yufeng Miao, Wei Zhang +1

Long-horizon reinforcement learning (RL) for large language models faces critical scalability challenges from unbounded context growth, leading to context folding methods that comp…

cs.CV2025

InSight-o3: Empowering Multimodal Foundation Models with Generalized Visual Search

Kaican Li, Lewei Yao, Jiannan Wu +7

The ability for AI agents to "think with images" requires a sophisticated blend of reasoning and perception. However, current open multimodal agents still largely fall short on the…

cs.LG2025

MEPIC: Memory Efficient Position Independent Caching for LLM Serving

Qian Wang, Zahra Yousefijamarani, Morgan Lindsay Heisler +8

Modern LLM applications such as deep-research assistants, coding agents, and Retrieval-Augmented Generation (RAG) systems, repeatedly process long prompt histories containing share…