5 papers
Divergent Paths: Learning an Outcome-Predictive Representation of LLM Agent Trajectories
Alexander Gill, Guram Gogia, Francisco Guzmán
In this work, we reframe agentic trajectories as paths through a shared embedding space of actions and environmental observations. We show that successful and failed rollouts of th…
Hand-Object Interaction in the Age of Large Foundation Models:Reconstruction, Generation, and Embodied Transfer
Weiquan Lin, Yu Deng, Shiyang Liu +6
Hand-object interaction (HOI) modeling remains challenging because it requires joint reasoning about hand articulation, object geometry, contact, semantics, and dynamics under seve…
Plug-and-Play Homeostatic Spark: Zero-Cost Acceleration for SNN Training Across Paradigms
Rui Chen, Xingyu Chen, Yaoqing Hu +3
Spiking neural networks offer event driven computation, sparse activation, and hardware efficiency, yet training often converges slowly and lacks stability. We present Adaptive Hom…
Detect Anything via Next Point Prediction
Qing Jiang, Junan Huo, Xingyu Chen +6
Object detection has long been dominated by traditional coordinate regression-based models, such as YOLO, DETR, and Grounding DINO. Although recent efforts have attempted to levera…
Rex-Thinker: Grounded Object Referring via Chain-of-Thought Reasoning
Qing Jiang, Xingyu Chen, Zhaoyang Zeng +2
Object referring aims to detect all objects in an image that match a given natural language description. We argue that a robust object referring model should be grounded, meaning i…