6 papers
Scaling Automatic Research Agents via World Models
Xiyuan Yang, Sheikh Sarwar, Jingru Cheng +7
Automating empirical research is a long-standing direction of AI. Recent automatic research (AutoResearch) agents bring this goal within reach, as modern LLMs show the capability t…
Latent Customer Segmentation and Value-Based Recommendation Leveraging a Two-Stage Model with Missing Labels
Keerthi Gopalakrishnan, Tianning Dong, Chia-Yen Ho +5
The success of businesses depends on their ability to convert consumers into loyal customers. A customer's value proposition is a primary determinant in this process, requiring a b…
Segment and Matte Anything in a Unified Model
Zezhong Fan, Xiaohan Li, Topojoy Biswas +2
Segment Anything (SAM) has recently pushed the boundaries of segmentation by demonstrating zero-shot generalization and flexible prompting after training on over one billion masks.…
Spatial Reasoning in Foundation Models: Benchmarking Object-Centric Spatial Understanding
Vahid Mirjalili, Ramin Giahi, Sriram Kollipara +9
Spatial understanding is a critical capability for vision foundation models. While recent advances in large vision models or vision-language models (VLMs) have expanded recognition…
LayoutAgent: A Vision-Language Agent Guided Compositional Diffusion for Spatial Layout Planning
Zezhong Fan, Xiaohan Li, Luyi Ma +6
Designing realistic multi-object scenes requires not only generating images, but also planning spatial layouts that respect semantic relations and physical plausibility. On one han…
CAL-RAG: Retrieval-Augmented Multi-Agent Generation for Content-Aware Layout Design
Najmeh Forouzandehmehr, Reza Yousefi Maragheh, Sriram Kollipara +4
Automated content-aware layout generation -- the task of arranging visual elements such as text, logos, and underlays on a background canvas -- remains a fundamental yet under-expl…