A comprehensive survey of artificial intelligence techniques for talent analytics

C Qin, L Zhang, Y Cheng, R Zha, D Shen… - arXiv preprint arXiv …, 2023 - arxiv.org
In today's competitive and fast-evolving business environment, it is a critical time for
organizations to rethink how to make talent-related decisions in a quantitative manner …

Generative ai for self-adaptive systems: State of the art and research roadmap

J Li, M Zhang, N Li, D Weyns, Z Jin, K Tei - ACM Transactions on …, 2024 - dl.acm.org
Self-adaptive systems (SASs) are designed to handle changes and uncertainties through a
feedback loop with four core functionalities: monitoring, analyzing, planning, and execution …

Fincon: A synthesized llm multi-agent system with conceptual verbal reinforcement for enhanced financial decision making

Y Yu, Z Yao, H Li, Z Deng, Y Cao, Z Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) have demonstrated notable potential in conducting complex
tasks and are increasingly utilized in various financial applications. However, high-quality …

AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversations

Q Wu, G Bansal, J Zhang, Y Wu, B Li, E Zhu… - First Conference on …, 2024 - openreview.net
We present AutoGen, an open-source framework that allows developers to build LLM
applications by composing multiple agents to converse with each other to accomplish tasks …

Generative AI Agents for Knowledge Work Augmentation in Finance

S Ganesh, L Ardon, D Borrajo, D Garg… - Annual Review of …, 2024 - annualreviews.org
The development of software agents that can autonomously take actions to achieve goals
has been a long-standing foundational objective in the field of AI. Recent advances in …

A Survey on Human-Centric LLMs

JY Wang, N Sukiennik, T Li, W Su, Q Hao, J Xu… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid evolution of large language models (LLMs) and their capacity to simulate human
cognition and behavior has given rise to LLM-based frameworks and tools that are …

Shall we team up: Exploring spontaneous cooperation of competing llm agents

Z Wu, R Peng, S Zheng, Q Liu, X Han… - Findings of the …, 2024 - aclanthology.org
Abstract Large Language Models (LLMs) have increasingly been utilized in social
simulations, where they are often guided by carefully crafted instructions to stably exhibit …

The landscape of emerging ai agent architectures for reasoning, planning, and tool calling: A survey

T Masterman, S Besen, M Sawtell, A Chao - arXiv preprint arXiv …, 2024 - arxiv.org
This survey paper examines the recent advancements in AI agent implementations, with a
focus on their ability to achieve complex goals that require enhanced reasoning, planning …

MHRC: Closed-loop Decentralized Multi-Heterogeneous Robot Collaboration with Large Language Models

W Yu, J Peng, Y Ying, S Li, J Ji, Y Zhang - arXiv preprint arXiv:2409.16030, 2024 - arxiv.org
The integration of large language models (LLMs) with robotics has significantly advanced
robots' abilities in perception, cognition, and task planning. The use of natural language …

BMW Agents--A Framework For Task Automation Through Multi-Agent Collaboration

N Crawford, EB Duffy, I Evazzade, T Foehr… - arXiv preprint arXiv …, 2024 - arxiv.org
Autonomous agents driven by Large Language Models (LLMs) offer enormous potential for
automation. Early proof of this technology can be found in various demonstrations of agents …