activity
20242026
most citedSAUP: Situation Awareness Uncertainty Propagation on LLM Agent

2 citations · 2 across the 2 of their papers we have counts for

collaborators

11 papers

cs.AI2026

Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement

Wangyang Ying, Yanchi Liu, Xujiang Zhao +5

Automatically extracting workflows as procedural graphs from natural language is promising yet underexplored, demanding both structural validity and logical alignment. While recent…

cs.LG2025

xTime: Extreme Event Prediction with Hierarchical Knowledge Distillation and Expert Fusion

Quan Li, Wenchao Yu, Suhang Wang +4

Extreme events frequently occur in real-world time series and often carry significant practical implications. In domains such as climate and healthcare, these events, such as flood…

cs.LG2025

SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search

Dong Li, Xujiang Zhao, Linlin Yu +7

Large Language Models (LLMs) offer promising capabilities for tackling complex reasoning tasks, including optimization problems. However, existing methods either rely on prompt eng…

cs.CL2025

Human Texts Are Outliers: Detecting LLM-generated Texts via Out-of-distribution Detection

Cong Zeng, Shengkun Tang, Yuanzhou Chen +6

The rapid advancement of large language models (LLMs) such as ChatGPT, DeepSeek, and Claude has significantly increased the presence of AI-generated text in digital communication.…

cs.LG2025

Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting

ChengAo Shen, Wenchao Yu, Ziming Zhao +4

Time series, typically represented as numerical sequences, can also be transformed into images and texts, offering multi-modal views (MMVs) of the same underlying signal. These MMV…

cs.LG2025

Where's the liability in the Generative Era? Recovery-based Black-Box Detection of AI-Generated Content

Haoyue Bai, Yiyou Sun, Wei Cheng +1

The recent proliferation of photorealistic images created by generative models has sparked both excitement and concern, as these images are increasingly indistinguishable from real…