activity
20232026
most citedPersonal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

31 citations · 31 across the 8 of their papers we have counts for

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Showing cs.AIShow all

5 papers · 1 filter

cs.AI2026

AOHP: An Open-Source OS-Level Agent Harness for Personalized, Efficient and Secure Interaction

Shanhui Zhao, Jiacheng Liu, Guohong Liu +13

AI agents are driving a new software paradigm, with the ability to autonomously call tools, extract information, manage memory, and complete tasks that span applications and data s…

cs.AI2026

Joint Agent Memory and Exploration Learning via Novelty Signals

Shizuo Tian, Xiaohong Weng, Rui Kong +9

In open-ended environments, exploration is fundamental for autonomous agents, yet current language model agents struggle with this. Effective exploration requires memory, but retai…

cs.AI2025

AgentProg: Empowering Long-Horizon GUI Agents with Program-Guided Context Management

Shizuo Tian, Hao Wen, Yuxuan Chen +6

The rapid development of mobile GUI agents has stimulated growing research interest in long-horizon task automation. However, building agents for these tasks faces a critical bottl…

cs.AI2025

GRAIL:Learning to Interact with Large Knowledge Graphs for Retrieval Augmented Reasoning

Ge Chang, Jinbo Su, Jiacheng Liu +7

Large Language Models (LLMs) integrated with Retrieval-Augmented Generation (RAG) techniques have exhibited remarkable performance across a wide range of domains. However, existing…

cs.AI2025

An Empirical Study of LLM Reasoning Ability Under Strict Output Length Constraint

Yi Sun, Han Wang, Jiaqiang Li +8

Recent work has demonstrated the remarkable potential of Large Language Models (LLMs) in test-time scaling. By making models think before answering, they are able to achieve much h…