· ai
[Paper] Equilibrium Propagation Without Limits
We liberate Equilibrium Propagation (EP) from the limit of infinitesimal perturbations by establishing a finite-nudge foundation for local credit assignment. By...
-
- · ai
[Paper] Revisiting Generalization Across Difficulty Levels: It's Not So Easy
We investigate how well large language models (LLMs) generalize across different task difficulties, a key question for effective data curation and evaluation. E...
- · ai
[Paper] Canvas-to-Image: Compositional Image Generation with Multimodal Controls
While modern diffusion models excel at generating high-quality and diverse images, they still struggle with high-fidelity compositional and multimodal control, ...
- · ai
[Paper] TraceGen: World Modeling in 3D Trace Space Enables Learning from Cross-Embodiment Videos
Learning new robot tasks on new platforms and in new scenes from only a handful of demonstrations remains challenging. While videos of other embodiments - human...
- · ai
[Paper] ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration
Large language models are powerful generalists, yet solving deep and complex problems such as those of the Humanity's Last Exam (HLE) remains both conceptually ...
- · ai
[Paper] G$^2$VLM: Geometry Grounded Vision Language Model with Unified 3D Reconstruction and Spatial Reasoning
Vision-Language Models (VLMs) still lack robustness in spatial intelligence, demonstrating poor performance on spatial understanding and reasoning tasks. We att...
- · ai
[Paper] Matrix: Peer-to-Peer Multi-Agent Synthetic Data Generation Framework
Synthetic data has become increasingly important for training large language models, especially when real data is scarce, expensive, or privacy-sensitive. Many ...
- · ai
[Paper] Seeing without Pixels: Perception from Camera Trajectories
Can one perceive a video's content without seeing its pixels, just from the camera trajectory-the path it carves through space? This paper is the first to syste...
- · ai
[Paper] Agentic Learner with Grow-and-Refine Multimodal Semantic Memory
MLLMs exhibit strong reasoning on isolated queries, yet they operate de novo -- solving each problem independently and often repeating the same mistakes. Existi...
- · ai
[Paper] On Evolution-Based Models for Experimentation Under Interference
Causal effect estimation in networked systems is central to data-driven decision making. In such settings, interventions on one unit can spill over to others, a...
- · ai
[Paper] Event-driven eligibility propagation in large sparse networks: efficiency shaped by biological realism
Despite remarkable technological advances, AI systems may still benefit from biological principles, such as recurrent connectivity and energy-efficient mechanis...
- · ai
[Paper] Revolutionizing Glioma Segmentation & Grading Using 3D MRI - Guided Hybrid Deep Learning Models
Gliomas are brain tumor types that have a high mortality rate which means early and accurate diagnosis is important for therapeutic intervention for the tumors....