Relative Position

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5 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

Jul 6Week of Sep 21

Latest papers 17

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Relative Transitions, Not Absolute Destinations: A Transfer-and-Ground Framework for Target-Trajectory-Free Human Mobility Generation
Oct 1, 2026Yidi Wang, Yunhe Zhang, Bangchao Deng +2Mobility Cities
SKL-IOTSC, Department of CIS, University of Macau Macau SAR, China
Who Is Left of Whom? Tracing Spatial Evidence and Role Binding in Relative-Position Reasoning
Sep 28, 2026Yingjin Song, Denis Paperno, Albert GattSpatial Reasoning Relative Position
Utrecht University Utrecht, The Netherlands
Relative Discharge Stage (RDS) Classification: A Practical Indicator of Battery Discharge Progress
Sep 23, 2026Khoa Tran, Tri Le, Hung-Cuong Trinh +1Lithium-Ion Batteries Prognostics
Data Science Laboratory, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, 70000, Vietnam · AIWARE Limited Company, 17 Huynh Man Dat Street, Hoa Cuong Ward, Hai Chau District, Da Nang, 550000, Vietnam · Natural Language Processing and Knowledge Discovery Research Group, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, 70000, Vietnam +2
Relative Contact Velocity-Controlled Hand-Object Mechanism for Dexterous Tool Manipulation
Sep 22, 2026Sunyu Wang, Jean Oh, Nancy S. PollardRobotic Hands Dexterous Manipulation
The authors are with the Robotics Institute at Carnegie Mellon University, Pittsburgh, USA.
Transformer-Informed Trajectory Optimization for Relative Motion in Cislunar Orbits
Sep 21, 2026Walter J. Manuel, Yuji Takubo, Simone D'AmicoIntent-Aligned Autonomous Spacecraft Guidance Robust Trajectory
Department of Aeronautics and Astronautics, Stanford University, Stanford, CA 94305
DCLP++: Learning to Navigate with Footprint Clearance and Relative Motion
Sep 8, 2026Shanze Wang, Wei ZhangDynamic Environments Footprint
College of Information Science and Technology, Eastern Institute of Technology, Ningbo, China · Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Principia: Relational Physics Tests for Video Models
Sep 3, 2026Varun Varma Thozhiyoor, Shivam Tripathi, Venkatesh Babu Radhakrishnan +1Generative Video Models Physics-Aware Models
Indian Institute of Science · Johns Hopkins University
Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control
Aug 12, 2026Josef Liyanjun ChenCpu-Gpu Hybrid Designs Cohort
Independent Researcher
Position Encoding in Transformers: From Absolute and Relative Methods to Rotary Position Embeddings and Long-Context Scaling
Aug 9, 2026Jiguo LiRotary Position Embedding Positional Encoding
Journey Operators for Structured Multi-Axis Composition
Jul 29, 2026Mahesh GodavartiRotary Position Embedding Relative Position
A Carrot, Inc
Relative Positions Generalize, Absolute Positions Memorize: An Implicit-Bias Account of Length Generalization in Attention
Jul 21, 2026Subham Singh, Ashutosh Mishra, Subha RautPositional Encoding Relative Position
Department of Mathematics and Statistics, Mississippi State University · Independent Researcher
Measuring Intelligence Beyond Human Scale
Jul 8, 2026Jerry Han, Rafael Moschopoulos, Ella Colby +5General Intelligence Psychometric Properties
Princeton Superalignment
Empowering a Single-Frequency GNSS Receiver to Achieve High-Precision Positioning with Relative Observations
Jun 28, 2026Xingpeng Wang, Ziwen Qu, Juncheng Chen +8Global Navigation Satellite System Relative Position
State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou, China · Huzhou Institute of Zhejiang University, Huzhou, China
Leveraging Metric Depth for Relative Depth Prediction
Jun 9, 2026Xiaoyang Bi, Shuaikun Liu, Zhaohong Liu +5Monocular Depth Estimation Dense Prediction
Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia · Beijing University of Posts and Telecommunications
$R^3$ : 3D Reconstruction via Relative Regression
May 26, 2026Congrong Xu, Huachen Gao, Xingyu Chen +3Feed-Forward 3D Reconstruction 3D Reconstruction
University of Michigan · Westlake University · NVIDIA
Jordan-RoPE: Non-Semisimple Relative Positional Encoding via Complex Jordan Blocks
May 5, 2026Yaobo ZhangPositional Encoding Relative Position
School of Physics, Ningxia University Yinchuan, 750021, China
URoPE: Universal Relative Position Embedding across Geometric Spaces
Apr 20, 2026Yichen Xie, Depu Meng, Chensheng Peng +4Visual Geometry Grounded Transformer Rotary Position Embedding
Applied Intuition · University of California, Berkeley

Oct 1, 2026, cs.LGJ/K move · Enter open · S save

Relative Transitions, Not Absolute Destinations: A Transfer-and-Ground Framework for Target-Trajectory-Free Human Mobility Generation

Yidi Wang, Yunhe Zhang, Bangchao Deng, Dingqi Yang+1

SKL-IOTSC, Department of CIS, University of Macau Macau SAR, China

Mobility Cities Absolute Pose Relative Position

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Individual mobility trajectories support urban analysis and location-based services, yet most trajectory generators require observations from their deployment city. This assumption excludes precisely the cities where trajectories are unavailable even though points of interest (POIs) and their attributes can be obtained from public maps. We study target-trajectory-free generation: learning from POIs and trajectories in source cities while utilizing only POI coordinates and categories in a target city, with no target trajectory or trajectory-derived statistic available for training, model selection, or generation. Existing trajectory generators typically predict absolute destinations, entangling reusable movement behavior with city-specific POI identities and spatial layouts. Our core insight is to replace this city-bound output with context-conditioned relative transitions. We propose Nomad, a transfer-and-ground framework that separates learning how people move from determining where those movements are realized. Specifically, a history-conditioned flow-matching model learns from source trajectories a transition prior over semantic displacement between POI contexts, geographic displacement, and elapsed time; at inference, a behavior graph and an exploration--return walk ground sampled transitions onto the target POI map. This factorization enables a direct test of representation level transferability without assuming invariance of the full mobility distribution. Extensive experiments across ten cities and 14 transfers show that Nomad outperforms adaptation baselines in trajectory fidelity and downstream utility, lowering the average error over the best baseline of each metric by about 15% in distributional fidelity and about 3% in downstream utility.

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