1 citations · 1 across the 4 of their papers we have counts for
4 papers
Using Semantic Distance to Estimate Uncertainty in LLM-Based Code Generation
Weilin He, Arindam Sharma, Cristina David
LLMs show strong performance in code generation, but their outputs lack correctness guarantees. Sample-based uncertainty estimators address this by generating multiple candidate pr…
TreeCoder: Systematic Exploration and Optimisation of Decoding and Constraints for LLM Code Generation
Henrijs Princis, Arindam Sharma, Cristina David
Large language models (LLMs) have shown remarkable ability to generate code, yet their outputs often violate syntactic or semantic constraints when guided only through natural lang…
Assessing Correctness in LLM-Based Code Generation via Uncertainty Estimation
Arindam Sharma, Cristina David
In this work, we explore uncertainty estimation as a proxy for correctness in LLM-generated code. To this end, we adapt two state-of-the-art techniques from natural language genera…
Enhancing SQL Query Generation with Neurosymbolic Reasoning
Henrijs Princis, Cristina David, Alan Mycroft
Neurosymbolic approaches blend the effectiveness of symbolic reasoning with the flexibility of neural networks. In this work, we propose a neurosymbolic architecture for generating…