2 citations · 4 across the 9 of their papers we have counts for
10 papers
MobileWorldBench: Towards Semantic World Modeling For Mobile Agents
Shufan Li, Konstantinos Kallidromitis, Akash Gokul +3
World models have shown great utility in improving the task performance of embodied agents. While prior work largely focuses on pixel-space world models, these approaches face prac…
UniEgoMotion: A Unified Model for Egocentric Motion Reconstruction, Forecasting, and Generation
Chaitanya Patel, Hiroki Nakamura, Yuta Kyuragi +3
Egocentric human motion generation and forecasting with scene-context is crucial for enhancing AR/VR experiences, improving human-robot interaction, advancing assistive technologie…
LaViDa: A Large Diffusion Language Model for Multimodal Understanding
Shufan Li, Konstantinos Kallidromitis, Hritik Bansal +7
Modern Vision-Language Models (VLMs) can solve a wide range of tasks requiring visual reasoning. In real-world scenarios, desirable properties for VLMs include fast inference and c…
VideoMultiAgents: A Multi-Agent Framework for Video Question Answering
Noriyuki Kugo, Xiang Li, Zixin Li +9
Video Question Answering (VQA) inherently relies on multimodal reasoning, integrating visual, temporal, and linguistic cues to achieve a deeper understanding of video content. Howe…
Reflect-DiT: Inference-Time Scaling for Text-to-Image Diffusion Transformers via In-Context Reflection
Shufan Li, Konstantinos Kallidromitis, Akash Gokul +4
The predominant approach to advancing text-to-image generation has been training-time scaling, where larger models are trained on more data using greater computational resources. W…
OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows
Shufan Li, Konstantinos Kallidromitis, Akash Gokul +4
We introduce OmniFlow, a novel generative model designed for any-to-any generation tasks such as text-to-image, text-to-audio, and audio-to-image synthesis. OmniFlow advances the r…
SegLLM: Multi-round Reasoning Segmentation
XuDong Wang, Shaolun Zhang, Shufan Li +5
We present SegLLM, a novel multi-round interactive reasoning segmentation model that enhances LLM-based segmentation by exploiting conversational memory of both visual and textual…
Few-Shot Classification of Interactive Activities of Daily Living (InteractADL)
Zane Durante, Robathan Harries, Edward Vendrow +5
Understanding Activities of Daily Living (ADLs) is a crucial step for different applications including assistive robots, smart homes, and healthcare. However, to date, few benchmar…
Aligning Diffusion Models by Optimizing Human Utility
Shufan Li, Konstantinos Kallidromitis, Akash Gokul +2
We present Diffusion-KTO, a novel approach for aligning text-to-image diffusion models by formulating the alignment objective as the maximization of expected human utility. Since t…
Wild2Avatar: Rendering Humans Behind Occlusions
Tiange Xiang, Adam Sun, Scott Delp +3
Rendering the visual appearance of moving humans from occluded monocular videos is a challenging task. Most existing research renders 3D humans under ideal conditions, requiring a…