14 citations · 20 across the 15 of their papers we have counts for
4 papers · 1 filter
VLM Agents Generate Their Own Memories: Distilling Experience into Embodied Programs of Thought
Gabriel Sarch, Lawrence Jang, Michael J. Tarr +3
Large-scale generative language and vision-language models (LLMs and VLMs) excel in few-shot learning but require high-quality demonstrations. We propose In-Context Abstraction Lea…
Reanimating Images using Neural Representations of Dynamic Stimuli
Jacob Yeung, Andrew F. Luo, Gabriel Sarch +3
While computer vision models have made incredible strides in static image recognition, they still do not match human performance in tasks that require the understanding of complex,…
HELPER-X: A Unified Instructable Embodied Agent to Tackle Four Interactive Vision-Language Domains with Memory-Augmented Language Models
Gabriel Sarch, Sahil Somani, Raghav Kapoor +2
Recent research on instructable agents has used memory-augmented Large Language Models (LLMs) as task planners, a technique that retrieves language-program examples relevant to the…
ODIN: A Single Model for 2D and 3D Segmentation
Ayush Jain, Pushkal Katara, Nikolaos Gkanatsios +5
State-of-the-art models on contemporary 3D segmentation benchmarks like ScanNet consume and label dataset-provided 3D point clouds, obtained through post processing of sensed multi…