2 citations · 2 across the 7 of their papers we have counts for
8 papers
SonicWorld: Source-Centric Latent Dynamics for Spatial Audio Reasoning
Chenlong Wei, Hanling Wang, Mingjin Lou +6
Dynamic spatial audio reasoning requires a model to associate changing acoustic observations with the correct source and recover its spatial state at a queried time or interval, a…
SPARROW: Scalable Taxonomy Induction via Structure-Preserving Partitioning and Constraint-Guided Merging
Yirui Zhang, Yixuan Tang, Yandong Sun +2
Taxonomy induction aims to organize concept sets into coherent hierarchical structures. Recent LLM-based methods can induce taxonomies directly from flat term lists, avoiding the n…
Emergency Preemption Without Online Exploration: A Decision Transformer Approach
Haoran Su, Hanxiao Deng, Yandong Sun
Emergency vehicle (EV) response time is a critical determinant of survival outcomes, yet deployed signal preemption strategies remain reactive and uncontrollable. We propose a retu…
Asking the Right Questions: Ontology-Grounded Interpretable Embeddings for Biomedical Text
Yixuan Tang, Zhenghong Lin, Yandong Sun +3
While dense biomedical embeddings achieve strong performance, their opaque dimensions limit transparency in biomedical NLP. Recent question-based interpretable embeddings represent…
Spatiotemporal Decision Transformer for Traffic Coordination
Haoran Su, Yandong Sun, Hanxiao Deng
Traffic signal control is a critical challenge in urban transportation, requiring coordination among multiple intersections to optimize network-wide traffic flow. While reinforceme…
The End of Reward Engineering: How LLMs Are Redefining Multi-Agent Coordination
Haoran Su, Yandong Sun, Congjia Yu
Reward engineering, the manual specification of reward functions to induce desired agent behavior, remains a fundamental challenge in multi-agent reinforcement learning. This diffi…
One Swallow Does Not Make a Summer: Understanding Semantic Structures in Embedding Spaces
Yandong Sun, Qiang Huang, Ziwei Xu +3
Embedding spaces are fundamental to modern AI, translating raw data into high-dimensional vectors that encode rich semantic relationships. Yet, their internal structures remain opa…
Don't Reinvent the Wheel: Efficient Instruction-Following Text Embedding based on Guided Space Transformation
Yingchaojie Feng, Yiqun Sun, Yandong Sun +4
In this work, we investigate an important task named instruction-following text embedding, which generates dynamic text embeddings that adapt to user instructions, highlighting spe…