Add to ORKGPre-trained models of source code have gained widespread popularity in many code intelligence tasks. Recently, with the scaling of the model and corpus size, large language models have shown the ability of in-context learning (ICL). ICL employs task instructions and a few examples as demonstrations, and then inputs the demonstrations to the language models for making predictions. This new learning paradigm is training-free and has shown impressive performance in various natural language processing and code intelligence tasks. However, the performance of ICL heavily relies on the quality of demonstrations, e.g., the selected examples. It is important to systematically investigate how to construct a good demonstration for code-related tasks. ...
Pretrained large language models (LLMs) are strong in-context learners that are able to perform few-...
Recent Language Models (LMs) achieve breakthrough performance in code generation when trained on hum...
Artificial intelligence (AI) for software engineering (SE) tasks has recently achieved promising per...
Large language models (LMs) are able to in-context learn -- perform a new task via inference alone b...
In-Context Learning (ICL) over Large language models (LLMs) aims at solving previously unseen tasks ...
In-context learning (ICL) i.e. showing LLMs only a few task-specific demonstrations has led to downs...
This paper systematically investigates the generation of code explanations by Large Language Models ...
Large language models have exhibited emergent abilities, demonstrating exceptional performance acros...
In-context learning (ICL) has become the default method for using large language models (LLMs), maki...
In this work, we evaluate 10 open-source instructed LLMs on four representative code comprehension a...
Large language models are able to perform a task by conditioning on a few input-output demonstration...
Large Language Models (LLM) are a new class of computation engines, "programmed" via prompt engineer...
With a handful of demonstration examples, large-scale language models show strong capability to perf...
Large Language models (LLMs) possess the capability to engage In-context Learning (ICL) by leveragin...
Machine-learning models can reach very high performance with supervised training, where they learn f...
Pretrained large language models (LLMs) are strong in-context learners that are able to perform few-...
Recent Language Models (LMs) achieve breakthrough performance in code generation when trained on hum...
Artificial intelligence (AI) for software engineering (SE) tasks has recently achieved promising per...
Large language models (LMs) are able to in-context learn -- perform a new task via inference alone b...
In-Context Learning (ICL) over Large language models (LLMs) aims at solving previously unseen tasks ...
In-context learning (ICL) i.e. showing LLMs only a few task-specific demonstrations has led to downs...
This paper systematically investigates the generation of code explanations by Large Language Models ...
Large language models have exhibited emergent abilities, demonstrating exceptional performance acros...
In-context learning (ICL) has become the default method for using large language models (LLMs), maki...
In this work, we evaluate 10 open-source instructed LLMs on four representative code comprehension a...
Large language models are able to perform a task by conditioning on a few input-output demonstration...
Large Language Models (LLM) are a new class of computation engines, "programmed" via prompt engineer...
With a handful of demonstration examples, large-scale language models show strong capability to perf...
Large Language models (LLMs) possess the capability to engage In-context Learning (ICL) by leveragin...
Machine-learning models can reach very high performance with supervised training, where they learn f...
Pretrained large language models (LLMs) are strong in-context learners that are able to perform few-...
Recent Language Models (LMs) achieve breakthrough performance in code generation when trained on hum...
Artificial intelligence (AI) for software engineering (SE) tasks has recently achieved promising per...