CodeInsight: A Curated Dataset of Practical Coding Solutions from Stack Overflow
We introduce a novel dataset tailored for code generation, aimed at aiding developers in
common tasks. Our dataset provides examples that include a clarified intent, code snippets …
common tasks. Our dataset provides examples that include a clarified intent, code snippets …
Skip-Layer Attention: Bridging Abstract and Detailed Dependencies in Transformers
Q Chen, W Wang, Q Zhang, S Zheng, S Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
The Transformer architecture has significantly advanced deep learning, particularly in natural
language processing, by effectively managing long-range dependencies. However, as the …
language processing, by effectively managing long-range dependencies. However, as the …
Qwen2 technical report
This report introduces the Qwen2 series, the latest addition to our large language models
and large multimodal models. We release a comprehensive suite of foundational and …
and large multimodal models. We release a comprehensive suite of foundational and …
A Software Engineering Perspective on Testing Large Language Models: Research, Practice, Tools and Benchmarks
… Parish, Emy Parparita, Alex Passos, Mikhail Pavlov, Andrew Peng, Adam Perelman, Filipe
de Avila Belbute Peres, Michael Petrov, Henrique Ponde de Oliveira Pinto, Michael, Pokorny, …
de Avila Belbute Peres, Michael Petrov, Henrique Ponde de Oliveira Pinto, Michael, Pokorny, …
Yi: Open foundation models by 01. ai
We introduce the Yi model family, a series of language and multimodal models that
demonstrate strong multi-dimensional capabilities. The Yi model family is based on 6B and 34B …
demonstrate strong multi-dimensional capabilities. The Yi model family is based on 6B and 34B …
Wizardcoder: Empowering code large language models with evol-instruct
Code Large Language Models (Code LLMs), such as StarCoder, have demonstrated
exceptional performance in code-related tasks. However, most existing models are solely pre-…
exceptional performance in code-related tasks. However, most existing models are solely pre-…
Data-juicer: A one-stop data processing system for large language models
… The statistical information can be generated and consumed by Data-Juicer’s other OPs
and tools, and we will describe more details of them in later sections. This interface works at …
and tools, and we will describe more details of them in later sections. This interface works at …
Satlm: Satisfiability-aided language models using declarative prompting
Prior work has combined chain-of-thought prompting in large language models (LLMs) with
programmatic representations to perform effective and transparent reasoning. While such an …
programmatic representations to perform effective and transparent reasoning. While such an …
Large language models for mathematical reasoning: Progresses and challenges
Mathematical reasoning serves as a cornerstone for assessing the fundamental cognitive
capabilities of human intelligence. In recent times, there has been a notable surge in the …
capabilities of human intelligence. In recent times, there has been a notable surge in the …
How Many Demonstrations Do You Need for In-context Learning?
Large language models (LLMs) are capable to perform complex reasoning by in-context
learning (ICL) when provided with a few input-output demonstrations (demos) and more …
learning (ICL) when provided with a few input-output demonstrations (demos) and more …