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Collections including paper arxiv:2107.03374

Code LMs Evaluation

A Survey on Language Models for Code

Paper • 2311.07989 • Published Nov 14, 2023 • 21
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Paper • 2310.06770 • Published Oct 10, 2023 • 3
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution

Paper • 2401.03065 • Published Jan 5 • 10
Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming

Paper • 2402.14261 • Published Feb 22 • 10

Papers - Testing a Coding Model

Evaluating Large Language Models Trained on Code

Paper • 2107.03374 • Published Jul 7, 2021 • 6

gemma_knowledg_tree

Gemini: A Family of Highly Capable Multimodal Models

Paper • 2312.11805 • Published Dec 19, 2023 • 44
Measuring Massive Multitask Language Understanding

Paper • 2009.03300 • Published Sep 7, 2020 • 3
HellaSwag: Can a Machine Really Finish Your Sentence?

Paper • 1905.07830 • Published May 19, 2019 • 4
PIQA: Reasoning about Physical Commonsense in Natural Language

Paper • 1911.11641 • Published Nov 26, 2019 • 2

cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser

Text Generation • Updated Mar 4 • 5.39k • 114
Evaluating Large Language Models Trained on Code

Paper • 2107.03374 • Published Jul 7, 2021 • 6
CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Paper • 2002.08155 • Published Feb 19, 2020 • 2
code2seq: Generating Sequences from Structured Representations of Code

Paper • 1808.01400 • Published Aug 4, 2018 • 2

Model Benchmarking

Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection

Paper • 2304.01238 • Published Apr 3, 2023 • 2
The FinBen: An Holistic Financial Benchmark for Large Language Models

Paper • 2402.12659 • Published Feb 20 • 13
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization

Paper • 2402.13249 • Published Feb 20 • 10
Evaluating Large Language Models Trained on Code

Paper • 2107.03374 • Published Jul 7, 2021 • 6

a growing collection of arXiv papers read while learning ML 📜

SMOTE: Synthetic Minority Over-sampling Technique

Paper • 1106.1813 • Published Jun 9, 2011 • 1
Scikit-learn: Machine Learning in Python

Paper • 1201.0490 • Published Jan 2, 2012 • 1
Identity Mappings in Deep Residual Networks

Paper • 1603.05027 • Published Mar 16, 2016 • 2
Deep Residual Learning for Image Recognition

Paper • 1512.03385 • Published Dec 10, 2015 • 5

There's usually interesting papers in the model cards on the leaderboard: https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard

StarCoder: may the source be with you!

Paper • 2305.06161 • Published May 9, 2023 • 26
WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Paper • 2306.08568 • Published Jun 14, 2023 • 27
SantaCoder: don't reach for the stars!

Paper • 2301.03988 • Published Jan 9, 2023 • 6
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Paper • 2401.14196 • Published Jan 25 • 44

Evaluating Large Language Models Trained on Code

Paper • 2107.03374 • Published Jul 7, 2021 • 6

Code Evaluation

Collection of Papers on Code Evaluation (from code generation language models)

A Survey on Language Models for Code

Paper • 2311.07989 • Published Nov 14, 2023 • 21
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

Paper • 2102.04664 • Published Feb 9, 2021 • 2
Evaluating Large Language Models Trained on Code

Paper • 2107.03374 • Published Jul 7, 2021 • 6
Out of the BLEU: how should we assess quality of the Code Generation models?

Paper • 2208.03133 • Published Aug 5, 2022 • 2

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