mlsanityData to 14 Oct 2026

A Word is Worth 4-bit: Efficient Log Parsing with Binary Coded Decimal Recognition

arXiv 2506.01147 ↗First posted 1 Jun 2025cs.CL cs.LGcited by 0

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Abstract (arXiv)

System-generated logs are typically converted into categorical log templates through parsing. These templates are crucial for generating actionable insights in various downstream tasks. However, existing parsers often fail to capture fine-grained template details, leading to suboptimal accuracy and reduced utility in downstream tasks requiring precise pattern identification. We propose a character-level log parser utilizing a novel neural architecture that aggregates character embeddings. Our approach estimates a sequence of binary-coded decimals to achieve highly granular log templates extraction. Our low-resource character-level parser, tested on revised Loghub-2k and a manually annotated industrial dataset, matches LLM-based parsers in accuracy while outperforming semantic parsers in efficiency.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 18 of its 37 references that are in the map. First posted on arXiv 1 Jun 2025.

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18 of 37 references.

References · 18

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2021Calibrate Before Use: Improving Few-Shot Performance of Language Modelscited by 1,392
  3. 2019Three scenarios for continual learningcited by 614
  4. 2016End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRFcited by 341
  5. 2020Rethinking Positional Encoding in Language Pre-trainingcited by 197
  6. 2020Loghub: A Large Collection of System Log Datasets for AI-driven Log Analyticscited by 70
  7. 2019TENER: Adapting Transformer Encoder for Named Entity Recognitioncited by 69
  8. 2024Understanding the Performance and Estimating the Cost of LLM Fine-Tuningcited by 48
  9. 2023What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs?cited by 47
  10. 2023LILAC: Log Parsing using LLMs with Adaptive Parsing Cachecited by 32
  11. 2023Log Parsing with Prompt-based Few-shot Learningcited by 29
  12. 2022UniParser: A Unified Log Parser for Heterogeneous Log Datacited by 26
6 more
  1. 2023A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We?cited by 26
  2. 2020Self-Supervised Log Parsingcited by 23
  3. 2023Did We Miss Something Important? Studying and Exploring Variable-Aware Log Abstractioncited by 19
  4. 2021SemParser: A Semantic Parser for Log Analysiscited by 17
  5. 2023Log Parsing Evaluation in the Era of Modern Software Systemscited by 6
  6. 2024LogPTR: Variable-Aware Log Parsing with Pointer Networkcited by 2

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  1. 2024Log Parsing using LLMs with Self-Generated In-Context Learning and Self-Correction
  2. 2024Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging
  3. 2026CelerLog: Fast Log Parsing via Dynamic Routing ↗
  4. 2026On Sequence-to-Sequence Models for Automated Log Parsing
  5. 2024LibreLog: Accurate and Efficient Unsupervised Log Parsing Using Open-Source Large Language Models
  6. 2026Instruction-Tuned LLMs for Parsing and Mining Unstructured Logs on Leadership HPC Systems
  7. 2026SpikeLogBERT: Energy-Efficient Log Parsing Using Spiking Transformer Networks
  8. 2024LogEval: A Comprehensive Benchmark Suite for Large Language Models In Log Analysis