CAIN 2025
Sun 27 - Mon 28 April 2025 Ottawa, Ontario, Canada
co-located with ICSE 2025
Mon 28 Apr 2025 16:00 - 16:15 at 208 - Generative Model Engineering Chair(s): Manel Abdellatif

Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation. However, the quality of the generated code is heavily dependent on the structure and composition of the prompts used. Crafting high-quality prompts is a challenging task that requires significant knowledge and skills of prompt engineering. To advance the automation support for the prompt engineering for LLM-based code generation, we propose a novel solution Diffusion-Driven Prompt Tuning (DDPT) that learns how to generate optimal prompt embedding from Gaussian Noise to automate the prompt engineering for code generation. We evaluate the feasibility of diffusion-based optimization and abstract the optimal prompt embedding as a directional vector toward the optimal embedding. We use the code generation loss given by the LLMs to help the diffusion model to capture the distribution of optimal prompt embedding during training. The trained diffusion model can build a path from the noise distribution to the optimal distribution at the sampling phrase. The evaluation result enable us to assert that that DDPT helps improve the prompt optimization for code generation and diffusion-driven language modeling techniques.

Mon 28 Apr

Displayed time zone: Eastern Time (US & Canada) change

16:00 - 17:30
Generative Model EngineeringResearch and Experience Papers / Industry Talks at 208
Chair(s): Manel Abdellatif École de Technologie Supérieure
16:00
15m
Talk
DDPT: Diffusion Driven Prompt Tuning for Large Language Model Code Generation
Research and Experience Papers
Jinyang Li The University of Adelaide, Sangwon Hyun CREST, University of Adelaide, Muhammad Ali Babar School of Computer Science, The University of Adelaide
16:15
15m
Talk
Engineering LLM Powered Multi-agent Framework for Autonomous CloudOpsDistinguished paper Award Candidate
Research and Experience Papers
Kannan Parthasarathy MontyCloud, Karthik Vaidhyanathan IIIT Hyderabad, Rudra Dhar SERC, IIIT Hyderabad, India, Venkat Krishnamachari MontyCloud, Adyansh Kakran International Institute of Information Technology, Hyderabad, Sreemaee Akshathala IIIT Hyderabad, Shrikara Arun IIIT Hyderabad, Amey Karan IIIT Hyderabad, Basil Muhammed MontyCloud, Sumant Dubey MontyCloud, Mohan Veerubhotla MontyCloud
16:30
15m
Talk
Generating and Verifying Synthetic Datasets with Requirements Engineering
Research and Experience Papers
Lynn Vonderhaar Embry-Riddle Aeronautical University, Timothy Elvira Embry-Riddle Aeronautical University, Omar Ochoa Embry-Riddle Aeronautical University
Pre-print
16:45
15m
Talk
LLM-Based Safety Case Generation for Baidu Apollo: Are We There Yet?
Research and Experience Papers
Oluwafemi Odu York University, Alvine Boaye Belle York University, Song Wang York University
17:00
12m
Talk
SqPal - text to SQL GenAI tool for PayPal
Industry Talks
Dan Liyanage PayPal, Mahshid Moha PayPal, Sandy Suresh PayPal
17:12
18m
Other
Discussion
Research and Experience Papers

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