1 citations · 1 across the 3 of their papers we have counts for
5 papers
Dual-Foundation Models for Unsupervised Domain Adaptation
Yerin Cheon, Aruna Balasubramanian, Francois Rameau
Semantic segmentation provides pixel-level scene understanding essential for autonomous driving and fine-grained perception tasks. However, training segmentation models requires co…
UniMotion: Self-Supervised Learning for Cross-Domain IMU Motion Recognition
Prerna Khanna, Tanmay Srivastava, Shubham Jain +1
IMU-based gesture interfaces are being increasingly adopted as efficient, accessible, and intuitive alternatives to traditional input methods, such as touchscreens and voice. Howev…
Lost in Instructions: Study of Blind Users' Experiences with DIY Manuals and AI-Rewritten Instructions for Assembly, Operation, and Troubleshooting of Tangible Products
Monalika Padma Reddy, Aruna Balasubramanian, Jiawei Zhou +3
AI tools like ChatGPT and Be-My-AI are increasingly being used by blind individuals. Although prior work has explored their use in some Do-It-Yourself (DIY) tasks by blind individu…
Fine-Grained Energy Prediction For Parallellized LLM Inference With PIE-P
Anurag Dutt, Young Won Choi, Avirup Sil +3
With the widespread adoption of Large Language Models (LLMs), energy costs of running LLMs is quickly becoming a critical concern. However, precisely measuring the energy consumpti…
ProST: Progressive Sub-task Training for Pareto-Optimal Multi-agent Systems Using Small Language Models
Biddut Sarker Bijoy, Mohammad Saqib Hasan, Pegah Alipoormolabashi +3
Multi-agent systems with smaller language models (SLMs) present a viable alternative to single agent systems powered by large language models (LLMs) for addressing complex problems…