24 citations · 40 across the 17 of their papers we have counts for
24 papers
Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation
Bolin Lai, Felix Juefei-Xu, Miao Liu +8
Text-guided image manipulation has experienced notable advancement in recent years. In order to mitigate linguistic ambiguity, few-shot learning with visual examples has been appli…
Early Exit Is a Natural Capability in Transformer-based Models: An Empirical Study on Early Exit without Joint Optimization
Weiqiao Shan, Long Meng, Tong Zheng +5
Large language models (LLMs) exhibit exceptional performance across various downstream tasks. However, they encounter limitations due to slow inference speeds stemming from their e…
Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning
Bei Li, Tong Zheng, Rui Wang +8
Residual networks, as discrete approximations of Ordinary Differential Equations (ODEs), have inspired significant advancements in neural network design, including multistep method…
Translate-and-Revise: Boosting Large Language Models for Constrained Translation
Pengcheng Huang, Yongyu Mu, Yuzhang Wu +4
Imposing constraints on machine translation systems presents a challenging issue because these systems are not trained to make use of constraints in generating adequate, fluent tra…
LogEval: A Comprehensive Benchmark Suite for Large Language Models In Log Analysis
Tianyu Cui, Shiyu Ma, Ziang Chen +10
Log analysis is crucial for ensuring the orderly and stable operation of information systems, particularly in the field of Artificial Intelligence for IT Operations (AIOps). Large…
Revisiting Interpolation Augmentation for Speech-to-Text Generation
Chen Xu, Jie Wang, Xiaoqian Liu +6
Speech-to-text (S2T) generation systems frequently face challenges in low-resource scenarios, primarily due to the lack of extensive labeled datasets. One emerging solution is cons…