8 citations · 32 across the 32 of their papers we have counts for
35 papers
MolmoAct2: Action Reasoning Models for Real-world Deployment
Haoquan Fang, Jiafei Duan, Donovan Clay +26
Vision-Language-Action (VLA) models aim to provide a single generalist controller for robots, but today's systems fall short on the criteria that matter for real-world deployment.…
VideoNet: A Large-Scale Dataset for Domain-Specific Action Recognition
Tanush Yadav, Mohammadreza Salehi, Jae Sung Park +6
Videos are unique in their ability to capture actions which transcend multiple frames. Accordingly, for many years action recognition was the quintessential task for video understa…
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…
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…
MolmoB0T: Large-Scale Simulation Enables Zero-Shot Manipulation
Abhay Deshpande, Maya Guru, Rose Hendrix +23
A prevailing view in robot learning is that simulation alone is not enough; effective sim-to-real transfer is widely believed to require at least some real-world data collection or…
MolmoSpaces: A Large-Scale Open Ecosystem for Robot Navigation and Manipulation
Yejin Kim, Wilbert Pumacay, Omar Rayyan +23
Deploying robots at scale demands robustness to the long tail of everyday situations. The countless variations in scene layout, object geometry, and task specifications that charac…
Imitating What Works: Simulation-Filtered Modular Policy Learning from Human Videos
Albert J. Zhai, Kuo-Hao Zeng, Jiasen Lu +3
The ability to learn manipulation skills by watching videos of humans has the potential to unlock a new source of highly scalable data for robot learning. Here, we tackle prehensil…
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…
OlmoEarth: Stable Latent Image Modeling for Multimodal Earth Observation
Henry Herzog, Favyen Bastani, Yawen Zhang +23
Earth observation data presents a unique challenge: it is spatial like images, sequential like video or text, and highly multimodal. We present OlmoEarth: a multimodal, spatio-temp…
MolmoAct: Action Reasoning Models that can Reason in Space
Jason Lee, Jiafei Duan, Haoquan Fang +16
Reasoning is central to purposeful action, yet most robotic foundation models map perception and instructions directly to control, which limits adaptability, generalization, and se…
Synthetic Visual Genome
Jae Sung Park, Zixian Ma, Linjie Li +9
Reasoning over visual relationships-spatial, functional, interactional, social, etc.-is considered to be a fundamental component of human cognition. Yet, despite the major advances…
Contrastive Flow Matching
George Stoica, Vivek Ramanujan, Xiang Fan +3
Unconditional flow-matching trains diffusion models to transport samples from a source distribution to a target distribution by enforcing that the flows between sample pairs are un…
Convergent Functions, Divergent Forms
Hyeonseong Jeon, Ainaz Eftekhar, Aaron Walsman +3
We introduce LOKI, a compute-efficient framework for co-designing morphologies and control policies that generalize across unseen tasks. Inspired by biological adaptation -- where…
Eval3D: Interpretable and Fine-grained Evaluation for 3D Generation
Shivam Duggal, Yushi Hu, Oscar Michel +7
Despite the unprecedented progress in the field of 3D generation, current systems still often fail to produce high-quality 3D assets that are visually appealing and geometrically a…
DRAWER: Digital Reconstruction and Articulation With Environment Realism
Hongchi Xia, Entong Su, Marius Memmel +7
Creating virtual digital replicas from real-world data unlocks significant potential across domains like gaming and robotics. In this paper, we present DRAWER, a novel framework th…
Beyond the Frame: Generating 360 Panoramic Videos from Perspective Videos
Rundong Luo, Matthew Wallingford, Ali Farhadi +2
360° videos have emerged as a promising medium to represent our dynamic visual world. Compared to the "tunnel vision" of standard cameras, their borderless field of view offers a m…
OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens
Jiacheng Liu, Taylor Blanton, Yanai Elazar +28
We present OLMoTrace, the first system that traces the outputs of language models back to their full, multi-trillion-token training data in real time. OLMoTrace finds and shows ver…
MutaGReP: Execution-Free Repository-Grounded Plan Search for Code-Use
Zaid Khan, Ali Farhadi, Ranjay Krishna +3
When a human requests an LLM to complete a coding task using functionality from a large code repository, how do we provide context from the repo to the LLM? One approach is to add…
2 OLMo 2 Furious
Team OLMo, Pete Walsh, Luca Soldaini +40
We present OLMo 2, the next generation of our fully open language models. OLMo 2 includes a family of dense autoregressive language models at 7B, 13B and 32B scales with fully rele…
From an Image to a Scene: Learning to Imagine the World from a Million 360 Videos
Matthew Wallingford, Anand Bhattad, Aditya Kusupati +7
Three-dimensional (3D) understanding of objects and scenes play a key role in humans' ability to interact with the world and has been an active area of research in computer vision,…
The One RING: a Robotic Indoor Navigation Generalist
Ainaz Eftekhar, Rose Hendrix, Luca Weihs +11
Modern robots vary significantly in shape, size, and sensor configurations used to perceive and interact with their environments. However, most navigation policies are embodiment-s…
ActionAtlas: A VideoQA Benchmark for Domain-specialized Action Recognition
Mohammadreza Salehi, Jae Sung Park, Tanush Yadav +5
Our world is full of varied actions and moves across specialized domains that we, as humans, strive to identify and understand. Within any single domain, actions can often appear q…
Learning to Build by Building Your Own Instructions
Aaron Walsman, Muru Zhang, Adam Fishman +2
Structural understanding of complex visual objects is an important unsolved component of artificial intelligence. To study this, we develop a new technique for the recently propose…
FLaRe: Achieving Masterful and Adaptive Robot Policies with Large-Scale Reinforcement Learning Fine-Tuning
Jiaheng Hu, Rose Hendrix, Ali Farhadi +5
In recent years, the Robotics field has initiated several efforts toward building generalist robot policies through large-scale multi-task Behavior Cloning. However, direct deploym…