most citedMolmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding

1 citations · 1 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction

Jianing Zhang, Chenhao Zheng, Yajun Yang +10

Motion forecasting is central to visual intelligence: agents must anticipate how objects will move in order to plan actions, reason about physical interactions, and synthesize real…

cs.CV2026

Posterior Augmented Flow Matching

George Stoica, Sayak Paul, Matthew Wallingford +6

Flow matching (FM) trains a time-dependent vector field that transports samples from a simple prior to a complex data distribution. However, for high-dimensional images, each train…

cs.CV2026

WildDet3D: Scaling Promptable 3D Detection in the Wild

Weikai Huang, Jieyu Zhang, Sijun Li +15

Understanding objects in 3D from a single image is a cornerstone of spatial intelligence. A key step toward this goal is monocular 3D object detection--recovering the extent, locat…

cs.CV2026

MolmoWeb: Open Visual Web Agent and Open Data for the Open Web

Tanmay Gupta, Piper Wolters, Zixian Ma +13

Web agents--autonomous systems that navigate and execute tasks on the web on behalf of users--have the potential to transform how people interact with the digital world. However, t…

cs.CV2026

MolmoPoint: Better Pointing for VLMs with Grounding Tokens

Christopher Clark, Yue Yang, Jae Sung Park +8

Grounding has become a fundamental capability of vision-language models (VLMs). Most existing VLMs point by generating coordinates as part of their text output, which requires lear…

cs.CV2026

Unified Spatio-Temporal Token Scoring for Efficient Video VLMs

Jianrui Zhang, Yue Yang, Rohun Tripathi +5

Token pruning is essential for enhancing the computational efficiency of vision-language models (VLMs), particularly for video-based tasks where temporal redundancy is prevalent. P…

cs.CV2026

Synthetic Visual Genome 2: Extracting Large-scale Spatio-Temporal Scene Graphs from Videos

Ziqi Gao, Jieyu Zhang, Wisdom Oluchi Ikezogwo +10

We introduce Synthetic Visual Genome 2 (SVG2), a large-scale panoptic video scene graph dataset. SVG2 contains over 636K videos with 6.6M objects, 52.0M attributes, and 6.7M relati…

cs.CV2026★ 1 cited

Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding

Christopher Clark, Jieyu Zhang, Zixian Ma +18

Today's strongest video-language models (VLMs) remain proprietary. The strongest open-weight models either rely on synthetic data from proprietary VLMs, effectively distilling from…

cs.CV2025

Visual Representations inside the Language Model

Benlin Liu, Amita Kamath, Madeleine Grunde-McLaughlin +2

Despite interpretability work analyzing VIT encoders and transformer activations, we don't yet understand why Multimodal Language Models (MLMs) struggle on perception-heavy tasks.…

cs.CV2025

Synthetic Object Compositions for Scalable and Accurate Learning in Detection, Segmentation, and Grounding

Weikai Huang, Jieyu Zhang, Taoyang Jia +5

Visual grouping -- operationalized through tasks such as instance segmentation, visual grounding, and object detection -- enables applications ranging from robotic perception to ph…