3 papers
cs.IR2024
Improving FIM Code Completions via Context & Curriculum Based Learning
Hitesh Sagtani, Rishabh Mehrotra, Beyang Liu
Fill-in-the-Middle (FIM) models play a vital role in code completion tasks, leveraging both prefix and suffix context to provide more accurate and contextually relevant suggestions…
cs.IR2024
Crafting Tomorrow: The Influence of Design Choices on Fresh Content in Social Media Recommendation
Srijan Saket, Mohit Agarwal, Rishabh Mehrotra
The rise in popularity of social media platforms, has resulted in millions of new, content pieces being created every day. This surge in content creation underscores the need to pa…
cs.IR2024
AI-assisted Coding with Cody: Lessons from Context Retrieval and Evaluation for Code Recommendations
Jan Hartman, Rishabh Mehrotra, Hitesh Sagtani +5
In this work, we discuss a recently popular type of recommender system: an LLM-based coding assistant. Connecting the task of providing code recommendations in multiple formats to…