13 citations · 18 across the 9 of their papers we have counts for
10 papers
MapTrace: Scalable Data Generation for Route Tracing on Maps
Artemis Panagopoulou, Aveek Purohit, Achin Kulshrestha +2
While Multimodal Large Language Models have achieved human-like performance on many visual and textual reasoning tasks, their proficiency in fine-grained spatial understanding, suc…
Sensible Agent: A Framework for Unobtrusive Interaction with Proactive AR Agents
Geonsun Lee, Min Xia, Nels Numan +9
Proactive AR agents promise context-aware assistance, but their interactions often rely on explicit voice prompts or responses, which can be disruptive or socially awkward. We intr…
EgoSocial: Benchmarking Proactive Intervention Ability of Omnimodal LLMs via Egocentric Social Interaction Perception
Xijun Wang, Tanay Sharma, Achin Kulshrestha +3
As AR/VR technologies become integral to daily life, there's a growing need for AI that understands human social dynamics from an egocentric perspective. However, current LLMs ofte…
EgoTrigger: Toward Audio-Driven Image Capture for Human Memory Enhancement in All-Day Energy-Efficient Smart Glasses
Akshay Paruchuri, Sinan Hersek, Lavisha Aggarwal +6
All-day smart glasses are likely to emerge as platforms capable of continuous contextual sensing, uniquely positioning them for unprecedented assistance in our daily lives. Integra…
Steerable Chatbots: Exploring Personalization Control Interfaces via LLM Activation Steering
Jessica Y. Bo, Tianyu Xu, Ishan Chatterjee +3
Personalizing LLM responses typically requires users to articulate their preferences through prompting, which can be burdensome at cold start and difficult to articulate in natural…
Geometry Aware Passthrough Mitigates Cybersickness
Trishia El Chemaly, Mohit Goyal, Tinglin Duan +8
Virtual Reality headsets isolate users from the real-world by restricting their perception to the virtual-world. Video See-Through (VST) headsets address this by utilizing world-fa…
Omnia de EgoTempo: Benchmarking Temporal Understanding of Multi-Modal LLMs in Egocentric Videos
Chiara Plizzari, Alessio Tonioni, Yongqin Xian +2
Understanding fine-grained temporal dynamics is crucial in egocentric videos, where continuous streams capture frequent, close-up interactions with objects. In this work, we bring…
Gatekeeper: Improving Model Cascades Through Confidence Tuning
Stephan Rabanser, Nathalie Rauschmayr, Achin Kulshrestha +5
Large-scale machine learning models deliver strong performance across a wide range of tasks but come with significant computational and resource constraints. To mitigate these chal…
Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence
Shangbin Feng, Zifeng Wang, Yike Wang +9
We propose Model Swarms, a collaborative search algorithm to adapt LLMs via swarm intelligence, the collective behavior guiding individual systems. Specifically, Model Swarms start…
BRAVE: Broadening the visual encoding of vision-language models
Oğuzhan Fatih Kar, Alessio Tonioni, Petra Poklukar +3
Vision-language models (VLMs) are typically composed of a vision encoder, e.g. CLIP, and a language model (LM) that interprets the encoded features to solve downstream tasks. Despi…