most citedERNIE 5.0 Technical Report

2 citations · 2 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.LG2025

Decomposing Task Vectors for Refined Model Editing

Hamed Damirchi, Ehsan Abbasnejad, Zhen Zhang +1

Large pre-trained models have transformed machine learning, yet adapting these models effectively to exhibit precise, concept-specific behaviors remains a significant challenge. Ta…

cs.LG2025

The Quest for Winning Tickets in Low-Rank Adapters

Hamed Damirchi, Cristian Rodriguez-Opazo, Ehsan Abbasnejad +2

The Lottery Ticket Hypothesis (LTH) suggests that over-parameterized neural networks contain sparse subnetworks ("winning tickets") capable of matching full model performance when…

cs.SI2025

Language Model Perplexity Predicts Scientific Surprise and Transformative Impact

Zhen Zhang, James Evans

Scientific breakthroughs typically emerge through the surprising violation of established research ideas, yet quantifying surprise has remained elusive because it requires a cohere…

cs.LG2025

Online Pseudo-average Shifting Attention(PASA) for Robust Low-precision LLM Inference: Algorithms and Numerical Analysis

Long Cheng, Qichen Liao, Fan Wu +10

Attention calculation is extremely time-consuming for long-sequence inference tasks, such as text or image/video generation, in large models. To accelerate this process, we develop…