8 papers
When the Judge Should Not Decide: Evidence-Locked, Non-Compensatory Selection Bounds LLM-Judge Failure in Reasoning Pipelines
Yiyao Zhang, Diksha Goel, Hussain Ahmad +2
An LLM judge deployed inside a reasoning pipeline does not merely measure quality, it decides which answer ships. We show that the cost of that decision depends less on judge accur…
CausalNav: Reliability-Certified Causal World Models for Control under Physical-Parameter Shift
Yiyao Zhang, Diksha Goel, Hussain Ahmad +2
A world model is only useful for physical AI if it changes what the agent does, and only safe if it declines to do so when it is wrong. We study both halves of that requirement wit…
A Cross-graph Tuning-free GNN Prompting Framework
Yaqi Chen, Shixun Huang, Ryan Twemlow +6
GNN prompting aims to adapt models across tasks and graphs without requiring extensive retraining. However, most existing graph prompt methods still require task-specific parameter…
Graph-centric Cross-model Data Integration and Analytics in a Unified Multi-model Database
Zepeng Liu, Sheng Wang, Shixun Huang +6
Graph-centric cross-model data integration and analytics (GCDIA) refer to tasks that leverage the graph model as a central paradigm to integrate relevant information across heterog…
Updatable Balanced Index for Stable Streaming Similarity Search over Large-Scale Fresh Vectors
Yuhui Lai, Shixun Huang, Sheng Wang
As artificial intelligence gains more and more popularity, vectors are one of the most widely used data structures for services such as information retrieval and recommendation. Ap…
A Hybrid Deep Learning based Carbon Price Forecasting Framework with Structural Breakpoints Detection and Signal Denoising
Runsheng Ren, Jing Li, Yanxiu Li +5
Accurately forecasting carbon prices is essential for informed energy market decision-making, guiding sustainable energy planning, and supporting effective decarbonization strategi…