6 citations · 8 across the 5 of their papers we have counts for
5 papers
Why Do LLM-based Web Agents Fail? A Hierarchical Planning Perspective
Mohamed Aghzal, Gregory J. Stein, Ziyu Yao
Large language model (LLM) web agents are increasingly used for web navigation but remain far from human reliability on realistic, long-horizon tasks. Existing evaluations focus pr…
A Survey on Large Language Models for Automated Planning
Mohamed Aghzal, Erion Plaku, Gregory J. Stein +1
The planning ability of Large Language Models (LLMs) has garnered increasing attention in recent years due to their remarkable capacity for multi-step reasoning and their ability t…
Evaluating Vision-Language Models as Evaluators in Path Planning
Mohamed Aghzal, Xiang Yue, Erion Plaku +1
Despite their promise to perform complex reasoning, large language models (LLMs) have been shown to have limited effectiveness in end-to-end planning. This has inspired an intrigui…
Look Further Ahead: Testing the Limits of GPT-4 in Path Planning
Mohamed Aghzal, Erion Plaku, Ziyu Yao
Large Language Models (LLMs) have shown impressive capabilities across a wide variety of tasks. However, they still face challenges with long-horizon planning. To study this, we pr…
Can Large Language Models be Good Path Planners? A Benchmark and Investigation on Spatial-temporal Reasoning
Mohamed Aghzal, Erion Plaku, Ziyu Yao
Large language models (LLMs) have achieved remarkable success across a wide spectrum of tasks; however, they still face limitations in scenarios that demand long-term planning and…