Command Palette
Search for a command to run...
Papers
Daily updated cutting-edge AI research papers to help you keep up with the latest AI trends
papers

AesCode: Aesthetic Code Generation with Decoupled Cross-Modal Rewards

GreenWAM: A World Foundation Model for Robotics




























Urbex: Agentic Spatial Grounding for City-Scale 3D Scenes
Agent-Reflex: Teaching Language Agents to Act Reflectively
VideoJev: System One Model for Video Understanding and Interaction
Jeva: System One Models from First Principles
Multi-Stream Attention Residuals
VIS-Ground: Video Interactive Storytelling with Contextual Grounding
Thinking Inertia: LLMs Keep Thinking When Told Not To
SCALING AGENTIC DATA FOR LONG-HORIZON TERMINAL INTELLIGENCE
GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
AGENTSWE: CAN CODING AGENTS BUILD THE AGENT YOU ACTUALLY WANT?
VISIONWEAVE: WEAVING ELASTIC VISUAL REPRESENTATIONS AS A NATIVE CAPABILITY OF MLLMS
EmbodiedCLBench: Evaluating Continual Learning for Self-Evolving Embodied Agents
SOFTWAREGYM: SCALING COMPUTER-USE AGENT TRAINING WITH DIVERSE SYNTHESIZED SOFTWARE ENVIRONMENTS
Reflex: Visually Grounded Reactive Humanoid Control
S-Space: Exploring Spatial Workspace in Multimodal Language Models
DIFFUSIONART: EFFICIENT, STABLE AND SCALABLE REINFORCEMENT OF DIFFUSION MODELS
MULTI-AGENT EGOCENTRIC WORLD MODEL WITH FINE-GRAINED EMBODIED INTERACTION
SUPERNAV: AN AGENTIC NAVIGATION SYSTEM FOR ANY TASK IN ANY SCENE
MiMo-V2.6: Scaling Reinforcement Learning Towards Self-Improvement
TokenRouter: Efficient Serving System for Token-Level LLM Routing
AgentGarten: Code Worlds for Evolving Agents
From Traces to Agentic Worlds: Agentic Language World Models for Interactive Environment Simulation
H-JEPA: END-TO-END LEARNING OF HIERARCHICAL WORLD MODELS FOR VISUAL PLANNING
ID Balancing: Stable Training of Extremely Sparse MoE via PID-Based Load Control
GPU-Accelerated Astrodynamics World Models for Spacecraft Rendezvous and Proximity Operations
4DCodeBench: Benchmarking Agents on Inverse Graphics of Dynamic Scenes
QUESTIONING THE QUESTIONS: SUSTAINING SELF-EVOLUTION IN REASONING MODELS
DECEPEVAL: A BENCHMARK FOR EVALUATING DE-CEPTION IN LLM AGENTS