2 citations · 2 across the 5 of their papers we have counts for
6 papers
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…
Empowering Reliable Visual-Centric Instruction Following in MLLMs
Weilei He, Feng Ju, Zhiyuan Fan +3
Evaluating the instruction-following (IF) capabilities of Multimodal Large Language Models (MLLMs) is essential for rigorously assessing how faithfully model outputs adhere to user…
Agentic Learner with Grow-and-Refine Multimodal Semantic Memory
Weihao Bo, Shan Zhang, Yanpeng Sun +9
MLLMs exhibit strong reasoning on isolated queries, yet they operate de novo -- solving each problem independently and often repeating the same mistakes. Existing memory-augmented…
MAS-Bench: A Unified Benchmark for Shortcut-Augmented Hybrid Mobile GUI Agents
Pengxiang Zhao, Guangyi Liu, YaoZhen Liang +11
Shortcuts such as APIs and deep-links have emerged as efficient complements to flexible GUI operations, fostering a promising hybrid paradigm for MLLM-based mobile automation. Howe…
Target Semantics Clustering via Text Representations for Robust Universal Domain Adaptation
Weinan He, Zilei Wang, Yixin Zhang
Universal Domain Adaptation (UniDA) focuses on transferring source domain knowledge to the target domain under both domain shift and unknown category shift. Its main challenge lies…
CREAM: Consistency Regularized Self-Rewarding Language Models
Zhaoyang Wang, Weilei He, Zhiyuan Liang +5
Recent self-rewarding large language models (LLM) have successfully applied LLM-as-a-Judge to iteratively improve the alignment performance without the need of human annotations fo…