From the 2 of 10 linked papers with an AI index.
10 papers
Before Agents Speak: Pre-hoc Failure Risk Inference in Multi-Agent Systems
Shi Lin, Chenpei Wang, Peng Qian +4
The paper introduces HalluProp, a framework that predicts which agents in a large‑language‑model based multi‑agent system are likely to hallucinate and estimates the overall system…
Forecasting Trajectory-Level Safety Risks in Black-Box Multi-Turn Interactions
Shi Lin, Peng Qian, Dinghao Liu +5
The paper introduces Recast, a framework that predicts safety risks in multi‑turn interactions with large language models by forecasting how risks evolve over dialogue trajectories…
BIRD-INTERACT: Re-imagining Text-to-SQL Evaluation for Large Language Models via Lens of Dynamic Interactions
Nan Huo, Xiaohan Xu, Jinyang Li +21
Large language models (LLMs) have demonstrated remarkable performance on single-turn text-to-SQL tasks, but real-world database applications predominantly require multi-turn intera…
STEC: A Reference-Free Spatio-Temporal Entropy Coverage Metric for Evaluating Sampled Video Frames
Shih-Yao Lin
Frame sampling is a fundamental component in video understanding and video--language model pipelines, yet evaluating the quality of sampled frames remains challenging. Existing eva…
Web Fraud Attacks Against LLM-Driven Multi-Agent Systems
Dezhang Kong, Hujin Peng, Yilun Zhang +5
With the proliferation of LLM-driven multi-agent systems (MAS), the security of Web links has become a critical concern. Once MAS is induced to trust a malicious link, attackers ca…
A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures
Dezhang Kong, Shi Lin, Zhenhua Xu +16
In recent years, Large-Language-Model-driven AI agents have exhibited unprecedented intelligence and adaptability. Nowadays, agents are undergoing a new round of evolution. They no…