7 papers
Unlocking Multi-Spectral Data for Multi-Modal Models with Guided Inputs and Chain-of-Thought Reasoning
Dahun Kim, Ganesh Satish Mallya, Anelia Angelova
Multi-spectral imagery is a valuable input signal for Remote Sensing applications, such as land-use and land-cover classification and environmental monitoring. However, generalist…
MINERVA-Cultural: A Benchmark for Cultural and Multilingual Long Video Reasoning
Darshan Singh, Arsha Nagrani, Kawshik Manikantan +6
Recent advancements in video models have shown tremendous progress, particularly in long video understanding. However, current benchmarks predominantly feature western-centric data…
Zero-Shot Multi-Spectral Learning: Reimagining a Generalist Multimodal Gemini 2.5 Model for Remote Sensing Applications
Ganesh Mallya, Yotam Gigi, Dahun Kim +4
Multi-spectral imagery plays a crucial role in diverse Remote Sensing applications including land-use classification, environmental monitoring and urban planning. These images are…
Time-Scaling State-Space Models for Dense Video Captioning
AJ Piergiovanni, Ganesh Satish Mallya, Dahun Kim +1
Dense video captioning is a challenging video understanding task which aims to simultaneously segment the video into a sequence of meaningful consecutive events and to generate det…
Context-Adaptive Multi-Prompt Embedding with Large Language Models for Vision-Language Alignment
Dahun Kim, Anelia Angelova
We propose Context-Adaptive Multi-Prompt Embedding, a novel approach to enrich semantic representations in vision-language contrastive learning. Unlike standard CLIP-style models t…
VideoComp: Advancing Fine-Grained Compositional and Temporal Alignment in Video-Text Models
Dahun Kim, AJ Piergiovanni, Ganesh Mallya +1
We introduce VideoComp, a benchmark and learning framework for advancing video-text compositionality understanding, aimed at improving vision-language models (VLMs) in fine-grained…