2 citations · 2 across the 8 of their papers we have counts for
9 papers
Evolutionary Safety of Recursive Self-Improving AI: Taxonomy, Risk Discovery, and Evaluation
Chang Gong, Jingping Bi, Di Yao +6
Rapid advances in AI are bringing recursive self-improvement (RSI) closer to practice, with growing progress in model self-training, self-evolving agents, and automated AI developm…
ZenGen: Social Mind for LLMs
ZenGen Team, Ao Xiang, Bi Jingping +57
As large language models move from isolated task solving toward long-term service in human environments, they require social intelligence: the ability to infer mental states, track…
Traj-MLLM: Can Multimodal Large Language Models Reform Trajectory Data Mining?
Shuo Liu, Di Yao, Yan Lin +2
Building a general model capable of analyzing human trajectories across different geographic regions and different tasks becomes an emergent yet important problem for various appli…
GTool: Graph Enhanced Tool Planning with Large Language Model
Wenjie Chen, Wenbin Li, Di Yao +3
Tool planning with large language models (LLMs), referring to selecting, organizing, and preparing the tools necessary to complete a user request, bridges the gap between natural l…
CausalTAD: Causal Implicit Generative Model for Debiased Online Trajectory Anomaly Detection
Wenbin Li, Di Yao, Chang Gong +6
Trajectory anomaly detection, aiming to estimate the anomaly risk of trajectories given the Source-Destination (SD) pairs, has become a critical problem for many real-world applica…
Effective and Efficient Representation Learning for Flight Trajectories
Shuo Liu, Wenbin Li, Di Yao +1
Flight trajectory data plays a vital role in the traffic management community, especially for downstream tasks such as trajectory prediction, flight recognition, and anomaly detect…
PORCA: Root Cause Analysis with Partially Observed Data
Chang Gong, Di Yao, Jin Wang +6
Root Cause Analysis (RCA) aims at identifying the underlying causes of system faults by uncovering and analyzing the causal structure from complex systems. It has been widely used…
STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis
Wenbin Li, Di Yao, Ruibo Zhao +7
The rapid evolution of large language models (LLMs) holds promise for reforming the methodology of spatio-temporal data mining. However, current works for evaluating the spatio-tem…
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
Shuo Liu, Di Yao, Lanting Fang +5
Detecting anomaly edges for dynamic graphs aims to identify edges significantly deviating from the normal pattern and can be applied in various domains, such as cybersecurity, fina…