5 papers
Context-Augmented Code Generation Using Programming Knowledge Graphs
Shahd Seddik, Fahd Seddik, Iman Saberi +3
Large Language Models (LLMs) excel at code generation but struggle with complex problems. Retrieval-Augmented Generation (RAG) mitigates this issue by integrating external knowledg…
FISCAL: Financial Synthetic Claim-document Augmented Learning for Efficient Fact-Checking
Rishab Sharma, Iman Saberi, Elham Alipour +2
Financial applications of large language models (LLMs) require factual reliability and computational efficiency, yet current systems often hallucinate details and depend on prohibi…
Context-Augmented Code Generation Using Programming Knowledge Graphs
Iman Saberi, Fatemeh Fard
Large Language Models (LLMs) and Code-LLMs (CLLMs) have significantly improved code generation, but, they frequently face difficulties when dealing with challenging and complex pro…
Empirical Studies of Parameter Efficient Methods for Large Language Models of Code and Knowledge Transfer to R
Amirreza Esmaeili, Iman Saberi, Fatemeh H. Fard
Parameter Efficient Fine-Tuning (PEFT) methods are proposed as an alternative fine-tuning approach for Large Language Models (LLM) to minimize high training costs. While prior rese…
AdvFusion: Adapter-based Knowledge Transfer for Code Summarization on Code Language Models
Iman Saberi, Amirreza Esmaeili, Fatemeh Fard +1
Programming languages can benefit from one another by utilizing a pre-trained model for software engineering tasks such as code summarization and method name prediction. While full…