ConCodeEval: Evaluating Large Language Models for Code Constraints in Domain-Specific Languages (2025.acl-industry)
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Mehant Kammakomati, Sameer Pimparkhede, Srikanth G. Tamilselvam, Prince Kumar, Pushpak Bhattacharyya
| Challenge: | Large Language Models (LLMs) have demonstrated potential in code generation and natural language understanding, but they struggle with code constraints. |
| Approach: | They propose to use Large Language Models to handle constraints represented in code . they use JSON, YAML, XML, Python, and natural language to test their effectiveness . |
| Outcome: | The proposed benchmark shows that LLMs can handle code constraints better than natural language . the results suggest that conscious choice of representations can lead to optimal use of LLM in enterprise use cases involving code constraints. |
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