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Large language models for software engineering: A systematic literature review
Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …
Software Engineering (SE). Many recent publications have explored LLMs applied to …
A survey on large language models for software engineering
Software Engineering (SE) is the systematic design, development, maintenance, and
management of software applications underpinning the digital infrastructure of our modern …
management of software applications underpinning the digital infrastructure of our modern …
Mapcoder: Multi-agent code generation for competitive problem solving
Code synthesis, which requires a deep understanding of complex natural language problem
descriptions, generation of code instructions for complex algorithms and data structures, and …
descriptions, generation of code instructions for complex algorithms and data structures, and …
Moodv2: Masked image modeling for out-of-distribution detection
Artificial lights commonly leave strong lens flare artifacts on the images captured at night,
degrading both the visual quality and performance of vision algorithms. Existing flare …
degrading both the visual quality and performance of vision algorithms. Existing flare …
Quickllama: Query-aware inference acceleration for large language models
The capacity of Large Language Models (LLMs) to comprehend and reason over long
contexts is pivotal for advancements in diverse fields. Yet, they still stuggle with capturing …
contexts is pivotal for advancements in diverse fields. Yet, they still stuggle with capturing …
Tagclip: Improving discrimination ability of open-vocabulary semantic segmentation
Contrastive Language-Image Pre-training (CLIP) has recently shown great promise in pixel-
level zero-shot learning tasks. However, existing approaches utilizing CLIP's text and patch …
level zero-shot learning tasks. However, existing approaches utilizing CLIP's text and patch …
TagCLIP: improving discrimination ability of zero-shot semantic segmentation
Contrastive Language-Image Pre-training (CLIP) has recently shown great promise in pixel-
level zero-shot learning tasks. However, existing approaches utilizing CLIP's text and patch …
level zero-shot learning tasks. However, existing approaches utilizing CLIP's text and patch …
CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging
Large Language Models (LLMs) have made significant strides in code generation and
problem solving. Current approaches employ external tool-based iterative debuggers that …
problem solving. Current approaches employ external tool-based iterative debuggers that …
Exploring the Potential of Llama Models in Automated Code Refinement: A Replication Study
G Caumartin, Q Qin, S Chatragadda, J Panjrolia… - arxiv preprint arxiv …, 2024 - arxiv.org
Code reviews are an integral part of software development and have been recognized as a
crucial practice for minimizing bugs and favouring higher code quality. They serve as an …
crucial practice for minimizing bugs and favouring higher code quality. They serve as an …