Bin Han

Orcid: 0000-0002-5280-9456

Affiliations:
  • University of Washington, Seattle, WA, USA


According to our database1, Bin Han authored at least 13 papers between 2023 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Can Large Language Models Integrate Spatial Data? Empirical Insights into Reasoning Strengths and Computational Weaknesses.
CoRR, August, 2025

MMMG: a Comprehensive and Reliable Evaluation Suite for Multitask Multimodal Generation.
CoRR, May, 2025

Fragments to Facts: Partial-Information Fragment Inference from LLMs.
CoRR, May, 2025

Cross-Lingual Text Classification with Large Language Models.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Do Language Models Mirror Human Confidence? Exploring Psychological Insights to Address Overconfidence in LLMs.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Towards Zero-Shot Annotation of the Built Environment with Vision-Language Models (Vision Paper).
CoRR, 2024

Geospatial Imputation of Urban Mobility Data with Self-Supervised Learning.
Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

SARN: Structurally-Aware Recurrent Network for Spatio-Temporal Disaggregation.
Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, 2024

Towards Zero-Shot Annotation of the Built Environment with Vision-Language Models.
Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, 2024

Laboratory-Scale AI: Open-Weight Models are Competitive with ChatGPT Even in Low-Resource Settings.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023
Top-down Green-ups: Satellite Sensing and Deep Models to Predict Buffelgrass Phenology.
CoRR, 2023

Urban Spatiotemporal Data Synthesis via Neural Disaggregation.
CoRR, 2023

Adapting to Skew: Imputing Spatiotemporal Urban Data with 3D Partial Convolutions and Biased Masking.
CoRR, 2023


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