8 papers
Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI
Savvas Petridis, Michael Xieyang Liu, Alexander J. Fiannaca +2
As AI systems grow increasingly capable of operating for hours or days at a time, users' prompts are transforming into elaborate specifications for the AI to autonomously work on.…
Retriv at BLP-2025 Task 2: Test-Driven Feedback-Guided Framework for Bangla-to-Python Code Generation
K M Nafi Asib, Sourav Saha, Mohammed Moshiul Hoque
Large Language Models (LLMs) have advanced the automated generation of code from natural language prompts. However, low-resource languages (LRLs) like Bangla remain underrepresente…
RTTC: Reward-Guided Collaborative Test-Time Compute
J. Pablo Muñoz, Jinjie Yuan
Test-Time Compute (TTC) has emerged as a powerful paradigm for enhancing the performance of Large Language Models (LLMs) at inference, leveraging strategies such as Test-Time Train…
Gensors: Authoring Personalized Visual Sensors with Multimodal Foundation Models and Reasoning
Michael Xieyang Liu, Savvas Petridis, Vivian Tsai +4
Multimodal large language models (MLLMs), with their expansive world knowledge and reasoning capabilities, present a unique opportunity for end-users to create personalized AI sens…
The Evolution of LLM Adoption in Industry Data Curation Practices
Crystal Qian, Michael Xieyang Liu, Emily Reif +7
As large language models (LLMs) grow increasingly adept at processing unstructured text data, they offer new opportunities to enhance data curation workflows. This paper explores t…
In Situ AI Prototyping: Infusing Multimodal Prompts into Mobile Settings with MobileMaker
Savvas Petridis, Michael Xieyang Liu, Alexander J. Fiannaca +3
Recent advances in multimodal large language models (LLMs) have made it easier to rapidly prototype AI-powered features, especially for mobile use cases. However, gathering early,…