mlsanityData to 14 Oct 2026

Construction contract risk identification based on knowledge-augmented language model

arXiv 2309.12626 ↗First posted 22 Sep 2023cs.AI cs.CLcited by 5

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Abstract (arXiv)

Contract review is an essential step in construction projects to prevent potential losses. However, the current methods for reviewing construction contracts lack effectiveness and reliability, leading to time-consuming and error-prone processes. While large language models (LLMs) have shown promise in revolutionizing natural language processing (NLP) tasks, they struggle with domain-specific knowledge and addressing specialized issues. This paper presents a novel approach that leverages LLMs with construction contract knowledge to emulate the process of contract review by human experts. Our tuning-free approach incorporates construction contract domain knowledge to enhance language models for identifying construction contract risks. The use of a natural language when building the domain knowledge base facilitates practical implementation. We evaluated our method on real construction contracts and achieved solid performance. Additionally, we investigated how large language models employ logical thinking during the task and provide insights and recommendations for future research.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 28 of its 67 references that are in the map. First posted on arXiv 22 Sep 2023.

Builds on

28 of 67 references.

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Cited by year

Citing papers per year: 2024: 2; 2025: 3.

5 papers.

  1. 2024LLM-Generated Natural Language Meets Scaling Laws: New Explorations and Data Augmentation Methodscited by 8
  2. 2024Foundation Models for Autonomous Robots in Unstructured Environmentscited by 3
  3. 2025Fine-Tuning Large Language Models and Evaluating Retrieval Methods for Improved Question Answering on Building Codescited by 2
  4. 2025Can AI Master Construction Management (CM)? Benchmarking State-of-the-Art Large Language Models on CM Certification Examscited by 1
  5. 2025GRAPH-GRPO-LEX: Contract Graph Modeling and Reinforcement Learning with Group Relative Policy Optimizationcited by 1