AgentScope: A Flexible yet Robust Multi-Agent Platform
Fuente:
arXiv
Guardado en:
| Autores principales: | Gao, Dawei, Li, Zitao, Pan, Xuchen, Kuang, Weirui, Ma, Zhijian, Qian, Bingchen, Wei, Fei, Zhang, Wenhao, Xie, Yuexiang, Chen, Daoyuan, Yao, Liuyi, Peng, Hongyi, Zhang, Zeyu, Zhu, Lin, Cheng, Chen, Shi, Hongzhu, Li, Yaliang, Ding, Bolin, Zhou, Jingren |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Very Large-Scale Multi-Agent Simulation in AgentScope
por: Pan, Xuchen, et al.
Publicado: (2024)
por: Pan, Xuchen, et al.
Publicado: (2024)
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
por: Gao, Dawei, et al.
Publicado: (2025)
por: Gao, Dawei, et al.
Publicado: (2025)
KIMAs: A Configurable Knowledge Integrated Multi-Agent System
por: Li, Zitao, et al.
Publicado: (2025)
por: Li, Zitao, et al.
Publicado: (2025)
EE-Tuning: An Economical yet Scalable Solution for Tuning Early-Exit Large Language Models
por: Pan, Xuchen, et al.
Publicado: (2024)
por: Pan, Xuchen, et al.
Publicado: (2024)
Tree-based Models for Vertical Federated Learning: A Survey
por: Qian, Bingchen, et al.
Publicado: (2025)
por: Qian, Bingchen, et al.
Publicado: (2025)
Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources
por: Bai, Jiamu, et al.
Publicado: (2024)
por: Bai, Jiamu, et al.
Publicado: (2024)
Trinity-RFT: A General-Purpose and Unified Framework for Reinforcement Fine-Tuning of Large Language Models
por: Pan, Xuchen, et al.
Publicado: (2025)
por: Pan, Xuchen, et al.
Publicado: (2025)
Automated Profile Inference with Language Model Agents
por: Du, Yuntao, et al.
Publicado: (2025)
por: Du, Yuntao, et al.
Publicado: (2025)
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism
por: Chen, Yanxi, et al.
Publicado: (2023)
por: Chen, Yanxi, et al.
Publicado: (2023)
Provable Scaling Laws for the Test-Time Compute of Large Language Models
por: Chen, Yanxi, et al.
Publicado: (2024)
por: Chen, Yanxi, et al.
Publicado: (2024)
Agent-Oriented Planning in Multi-Agent Systems
por: Li, Ao, et al.
Publicado: (2024)
por: Li, Ao, et al.
Publicado: (2024)
BiMix: A Bivariate Data Mixing Law for Language Model Pretraining
por: Ge, Ce, et al.
Publicado: (2024)
por: Ge, Ce, et al.
Publicado: (2024)
The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective
por: Qin, Zhen, et al.
Publicado: (2024)
por: Qin, Zhen, et al.
Publicado: (2024)
On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting
por: Zhang, Wenhao, et al.
Publicado: (2025)
por: Zhang, Wenhao, et al.
Publicado: (2025)
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes
por: Qin, Zhen, et al.
Publicado: (2023)
por: Qin, Zhen, et al.
Publicado: (2023)
Learning Agent-Compatible Context Management for Long-Horizon Tasks
por: Yi, Lu, et al.
Publicado: (2026)
por: Yi, Lu, et al.
Publicado: (2026)
Efficient Leave-one-out Approximation in LLM Multi-agent Debate Based on Introspection
por: Cui, Yue, et al.
Publicado: (2025)
por: Cui, Yue, et al.
Publicado: (2025)
A Bargaining-based Approach for Feature Trading in Vertical Federated Learning
por: Cui, Yue, et al.
Publicado: (2024)
por: Cui, Yue, et al.
Publicado: (2024)
GenSim: A General Social Simulation Platform with Large Language Model based Agents
por: Tang, Jiakai, et al.
Publicado: (2024)
por: Tang, Jiakai, et al.
Publicado: (2024)
On the Convergence of Zeroth-Order Federated Tuning for Large Language Models
por: Ling, Zhenqing, et al.
Publicado: (2024)
por: Ling, Zhenqing, et al.
Publicado: (2024)
IntentRL: Training Proactive User-intent Agents for Open-ended Deep Research via Reinforcement Learning
por: Luo, Haohao, et al.
Publicado: (2026)
por: Luo, Haohao, et al.
Publicado: (2026)
Data-Juicer 2.0: Cloud-Scale Adaptive Data Processing for and with Foundation Models
por: Chen, Daoyuan, et al.
Publicado: (2024)
por: Chen, Daoyuan, et al.
Publicado: (2024)
Designing Algorithms Empowered by Language Models: An Analytical Framework, Case Studies, and Insights
por: Chen, Yanxi, et al.
Publicado: (2024)
por: Chen, Yanxi, et al.
Publicado: (2024)
Data-Juicer Sandbox: A Feedback-Driven Suite for Multimodal Data-Model Co-development
por: Chen, Daoyuan, et al.
Publicado: (2024)
por: Chen, Daoyuan, et al.
Publicado: (2024)
BOTS: A Unified Framework for Bayesian Online Task Selection in LLM Reinforcement Finetuning
por: Shen, Qianli, et al.
Publicado: (2025)
por: Shen, Qianli, et al.
Publicado: (2025)
Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents
por: Yu, Yi, et al.
Publicado: (2026)
por: Yu, Yi, et al.
Publicado: (2026)
Grounded in Reality: Learning and Deploying Proactive LLM from Offline Logs
por: Wei, Fei, et al.
Publicado: (2025)
por: Wei, Fei, et al.
Publicado: (2025)
Improving LoRA in Privacy-preserving Federated Learning
por: Sun, Youbang, et al.
Publicado: (2024)
por: Sun, Youbang, et al.
Publicado: (2024)
Exploring Selective Layer Fine-Tuning in Federated Learning
por: Sun, Yuchang, et al.
Publicado: (2024)
por: Sun, Yuchang, et al.
Publicado: (2024)
Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data
por: Ling, Zhenqing, et al.
Publicado: (2025)
por: Ling, Zhenqing, et al.
Publicado: (2025)
Group-Relative REINFORCE Is Secretly an Off-Policy Algorithm: Demystifying Some Myths About GRPO and Its Friends
por: Yao, Chaorui, et al.
Publicado: (2025)
por: Yao, Chaorui, et al.
Publicado: (2025)
LLM-Based Multi-Agent Systems are Scalable Graph Generative Models
por: Ji, Jiarui, et al.
Publicado: (2024)
por: Ji, Jiarui, et al.
Publicado: (2024)
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model
por: Wu, Feijie, et al.
Publicado: (2024)
por: Wu, Feijie, et al.
Publicado: (2024)
An Auction-based Marketplace for Model Trading in Federated Learning
por: Cui, Yue, et al.
Publicado: (2024)
por: Cui, Yue, et al.
Publicado: (2024)
Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models
por: Jiao, Qirui, et al.
Publicado: (2024)
por: Jiao, Qirui, et al.
Publicado: (2024)
HumanVBench: Probing Human-Centric Video Understanding in MLLMs with Automatically Synthesized Benchmarks
por: Zhou, Ting, et al.
Publicado: (2024)
por: Zhou, Ting, et al.
Publicado: (2024)
On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
por: Wang, Shumin, et al.
Publicado: (2026)
por: Wang, Shumin, et al.
Publicado: (2026)
Safety Layers in Aligned Large Language Models: The Key to LLM Security
por: Li, Shen, et al.
Publicado: (2024)
por: Li, Shen, et al.
Publicado: (2024)
Respecting Temporal-Causal Consistency: Entity-Event Knowledge Graphs for Retrieval-Augmented Generation
por: Zhang, Ze Yu, et al.
Publicado: (2025)
por: Zhang, Ze Yu, et al.
Publicado: (2025)
Retrieval Heads are Dynamic
por: Lin, Yuping, et al.
Publicado: (2026)
por: Lin, Yuping, et al.
Publicado: (2026)
Ejemplares similares
-
Very Large-Scale Multi-Agent Simulation in AgentScope
por: Pan, Xuchen, et al.
Publicado: (2024) -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
por: Gao, Dawei, et al.
Publicado: (2025) -
KIMAs: A Configurable Knowledge Integrated Multi-Agent System
por: Li, Zitao, et al.
Publicado: (2025) -
EE-Tuning: An Economical yet Scalable Solution for Tuning Early-Exit Large Language Models
por: Pan, Xuchen, et al.
Publicado: (2024) -
Tree-based Models for Vertical Federated Learning: A Survey
por: Qian, Bingchen, et al.
Publicado: (2025)