7 citations · 7 across the 17 of their papers we have counts for
7 papers · 1 filter
S-EMBER: A Large-Scale Benchmark for Streaming Egocentric Memory Retrieval
Xiaodong Wang, Xuanyi Zhao, Pedro Rodriguez +7
As wearable devices enable continuous first-person recording, AI assistants must reason across long time horizons to recall past experiences-a capability known as episodic memory.…
MoE-ViE: Mixture of Experts Vision Encoder for Efficient Image and Video Understanding
Bonan Zhang, Shiyu Dong, Quan Hung Tran +9
Vision encoders are a critical component of vision-language models, and scaling their capacity effectively improves performance. However, dense scaling increases compute cost and i…
R3D: Quantitative 3D Spatial Reasoning for Egocentric Wearables
Maxwell Horton, Wei Lu, Quan Tran +6
Quantitative 3D spatial reasoning from egocentric RGB-D video is a critical capability for next-generation wearable assistants. Yet existing benchmarks do not reflect the challenge…
Plan, Watch, Recover: A Benchmark and Architectures for Proactive Procedural Assistance
Kaustav Kundu, Ritvik Shrivastava, Maxim Arap +14
Proactive multimodal assistants must decide when guidance is needed and what to say, while tracking progress through extended procedures and helping users recover when they depart…
PixSearch: Region-Grounded Retrieval for Knowledgeable Large Multimodal Models
Jeonghwan Kim, Renjie Tao, Sanat Sharma +8
Multimodal Retrieval-Augmented Generation (MM-RAG) augments visual question answering (VQA) with external knowledge, but many systems rely on modular pipelines that separate visual…
VisualLens: Personalization through Task-Agnostic Visual History
Wang Bill Zhu, Deqing Fu, Kai Sun +8
Existing recommendation systems either rely on user interaction logs, such as online shopping history for shopping recommendations, or focus on text signals. However, item-based hi…
SnapNTell: Enhancing Entity-Centric Visual Question Answering with Retrieval Augmented Multimodal LLM
Jielin Qiu, Andrea Madotto, Zhaojiang Lin +7
Vision-extended LLMs have made significant strides in Visual Question Answering (VQA). Despite these advancements, VLLMs still encounter substantial difficulties in handling querie…