196 citations · 458 across the 30 of their papers we have counts for
42 papers
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…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
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…
Whats in a Video: Factorized Autoregressive Decoding for Online Dense Video Captioning
AJ Piergiovanni, Dahun Kim, Michael S. Ryoo +2
Generating automatic dense captions for videos that accurately describe their contents remains a challenging area of research. Most current models require processing the entire vid…
Mirasol3B: A Multimodal Autoregressive model for time-aligned and contextual modalities
AJ Piergiovanni, Isaac Noble, Dahun Kim +3
One of the main challenges of multimodal learning is the need to combine heterogeneous modalities (e.g., video, audio, text). For example, video and audio are obtained at much high…
Diversifying Joint Vision-Language Tokenization Learning
Vardaan Pahuja, AJ Piergiovanni, Anelia Angelova
Building joint representations across images and text is an essential step for tasks such as Visual Question Answering and Video Question Answering. In this work, we find that the…