# UniLog: Deploy One Model and Specialize it for All Log Analysis Tasks

arXiv: https://arxiv.org/abs/2112.03159 · HTML: https://mlsanity.com/paper/2112.03159/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 20 of its 44 references that are in the map.
- First posted on arXiv 6 Dec 2021.

## Builds on (most cited first, 20 of 20)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [A Simple Framework for Contrastive Learning of Visual Representations](https://mlsanity.com/paper/2002.05709/) (2020)
- [Layer Normalization](https://mlsanity.com/paper/1607.06450/) (2016)
- [Decoupled Weight Decay Regularization](https://mlsanity.com/paper/1711.05101/) (2017)
- [On Layer Normalization in the Transformer Architecture](https://mlsanity.com/paper/2002.04745/) (2020)
- [Language Modeling with Gated Convolutional Networks](https://mlsanity.com/paper/1612.08083/) (2016)
- [Do Transformers Really Perform Bad for Graph Representation?](https://mlsanity.com/paper/2106.05234/) (2021)
- [Neural Architecture Search without Training](https://mlsanity.com/paper/2006.04647/) (2020)
- [To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks](https://mlsanity.com/paper/1903.05987/) (2019)
- [Fine-tune BERT for Extractive Summarization](https://mlsanity.com/paper/1903.10318/) (2019)
- [LogBERT: Log Anomaly Detection via BERT](https://mlsanity.com/paper/2103.04475/) (2021)
- [Tools and Benchmarks for Automated Log Parsing](https://mlsanity.com/paper/1811.03509/) (2018)
- [A Survey on Automated Log Analysis for Reliability Engineering](https://mlsanity.com/paper/2009.07237/) (2020)
- [Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression](https://mlsanity.com/paper/1910.00409/) (2019)
- [Summarizing Unstructured Logs in Online Services](https://mlsanity.com/paper/2012.08938/) (2020)

## Built on by (most cited first, 11 of 11)

- [AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges](https://mlsanity.com/paper/2304.04661/) (2023)
- [LogLM: From Task-based to Instruction-based Automated Log Analysis](https://mlsanity.com/paper/2410.09352/) (2024)
- [Large Language Models for Security Operations Centers: A Comprehensive Survey](https://mlsanity.com/paper/2509.10858/) (2025)
- [R-Log: Incentivizing Log Analysis Capability in LLMs via Reasoning-based Reinforcement Learning](https://mlsanity.com/paper/2509.25987/) (2025)
- [LogAI: A Library for Log Analytics and Intelligence](https://mlsanity.com/paper/2301.13415/) (2023)
- [LUK: Empowering Log Understanding with Expert Knowledge from Large Language Models](https://mlsanity.com/paper/2409.01909/) (2024)
- [Leveraging Log Instructions in Log-based Anomaly Detection](https://mlsanity.com/paper/2207.03206/) (2022)
- [Diagnosing and Resolving Cloud Platform Instability with Multi-modal RAG LLMs](https://mlsanity.com/paper/2505.21419/) (2025)
- [Embodiment Transfer Learning for Vision-Language-Action Models](https://mlsanity.com/paper/2511.01224/) (2025)
- [Failure Identification from Unstable Log Data using Deep Learning](https://mlsanity.com/paper/2204.02636/) (2022)
- [Interactive Log Parsing via Light-weight User Feedback](https://mlsanity.com/paper/2301.12225/) (2023)

## Abstract (arXiv)

UniLog: Deploy One Model and Specialize it for All Log Analysis Tasks