49 citations · 126 across the 6 of their papers we have counts for
6 papers
Less is More: Towards Green Code Large Language Models via Unified Structural Pruning
Guang Yang, Yu Zhou, Xiangyu Zhang +5
The extensive application of Large Language Models (LLMs) in generative coding tasks has raised concerns due to their high computational demands and energy consumption. Unlike prev…
Less is More: DocString Compression in Code Generation
Guang Yang, Yu Zhou, Wei Cheng +7
The widespread use of Large Language Models (LLMs) in software engineering has intensified the need for improved model and resource efficiency. In particular, for neural code gener…
Reasoning with Language Model Prompting: A Survey
Shuofei Qiao, Yixin Ou, Ningyu Zhang +6
Reasoning, as an essential ability for complex problem-solving, can provide back-end support for various real-world applications, such as medical diagnosis, negotiation, etc. This…
Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning
Xiang Chen, Lei Li, Ningyu Zhang +6
Prompt learning approaches have made waves in natural language processing by inducing better few-shot performance while they still follow a parametric-based learning paradigm; the…
LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Prompting
Xiang Chen, Lei Li, Shumin Deng +6
Most NER methods rely on extensive labeled data for model training, which struggles in the low-resource scenarios with limited training data. Existing dominant approaches usually s…
How convolutional neural network see the world - A survey of convolutional neural network visualization methods
Zhuwei Qin, Fuxun Yu, Chenchen Liu +1
Nowadays, the Convolutional Neural Networks (CNNs) have achieved impressive performance on many computer vision related tasks, such as object detection, image recognition, image re…