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20212024
most citedOpenAGI: When LLM Meets Domain Experts

76 citations · 278 across the 18 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

cs.CL2024★ 5 cited

AutoFlow: Automated Workflow Generation for Large Language Model Agents

Zelong Li, Shuyuan Xu, Kai Mei +6

Recent advancements in Large Language Models (LLMs) have shown significant progress in understanding complex natural language. One important application of LLM is LLM-based AI Agen…

cs.CL2024★ 1 cited

Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities

Wenyue Hua, Kaijie Zhu, Lingyao Li +7

This study intends to systematically disentangle pure logic reasoning and text understanding by investigating the contrast across abstract and contextualized logical problems from…

cs.CL2024★ 2 cited

AIOS Compiler: LLM as Interpreter for Natural Language Programming and Flow Programming of AI Agents

Shuyuan Xu, Zelong Li, Kai Mei +1

Since their inception, programming languages have trended towards greater readability and lower barriers for programmers. Following this trend, natural language can be a promising…

cs.IR2024★ 1 cited

IDGenRec: LLM-RecSys Alignment with Textual ID Learning

Juntao Tan, Shuyuan Xu, Wenyue Hua +3

Generative recommendation based on Large Language Models (LLMs) have transformed the traditional ranking-based recommendation style into a text-to-text generation paradigm. However…

cs.OS2024★ 9 cited

AIOS: LLM Agent Operating System

Kai Mei, Xi Zhu, Wujiang Xu +7

LLM-based intelligent agents face significant deployment challenges, particularly related to resource management. Allowing unrestricted access to LLM or tool resources can lead to…

cs.CL2024★ 2 cited

TrustAgent: Towards Safe and Trustworthy LLM-based Agents

Wenyue Hua, Xianjun Yang, Mingyu Jin +4

The rise of LLM-based agents shows great potential to revolutionize task planning, capturing significant attention. Given that these agents will be integrated into high-stake domai…

cs.LG2024★ 2 cited

Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents

Zelong Li, Wenyue Hua, Hao Wang +2

Recent advancements on Large Language Models (LLMs) enable AI Agents to automatically generate and execute multi-step plans to solve complex tasks. However, since LLM's content gen…

cs.IR2024★ 1 cited

PAP-REC: Personalized Automatic Prompt for Recommendation Language Model

Zelong Li, Jianchao Ji, Yingqiang Ge +2

Recently emerged prompt-based Recommendation Language Models (RLM) can solve multiple recommendation tasks uniformly. The RLMs make full use of the inherited knowledge learned from…