Imagen de Portada

On the Importance of Task Complexity in Evaluating LLM-Based Multi-Agent Systems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Tang, Bohan, Liang, Huidong, Jiang, Keyue, Dong, Xiaowen
Formato:	Preprint
Publicado:	2025
Materias:	Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Heterogeneous Graph Structure Learning through the Lens of Data-generating Processes
por: Jiang, Keyue, et al.
Publicado: (2025)

Training-Free Message Passing for Learning on Hypergraphs
por: Tang, Bohan, et al.
Publicado: (2024)

A Markov Random Field model for Hypergraph-based Machine Learning
por: Tang, Bohan, et al.
Publicado: (2023)

Bures-Wasserstein Flow Matching for Graph Generation
por: Jiang, Keyue, et al.
Publicado: (2025)

Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement
por: Liang, Huidong, et al.
Publicado: (2025)

Understanding Agent Scaling in LLM-Based Multi-Agent Systems via Diversity
por: Yang, Yingxuan, et al.
Publicado: (2026)

Decentralized and Lifelong-Adaptive Multi-Agent Collaborative Learning
por: Tang, Shuo, et al.
Publicado: (2024)

Active Learning for Communication Structure Optimization in LLM-Based Multi-Agent Systems
por: Yang, Huchen, et al.
Publicado: (2026)

LiveClawBench: Benchmarking LLM Agents on Complex, Real-World Assistant Tasks
por: Long, Xiang, et al.
Publicado: (2026)

TemporalBench: A Benchmark for Evaluating LLM-Based Agents on Contextual and Event-Informed Time Series Tasks
por: Weng, Muyan, et al.
Publicado: (2026)

BrowserArena: Evaluating LLM Agents on Real-World Web Navigation Tasks
por: Anupam, Sagnik, et al.
Publicado: (2025)

ARM: Discovering Agentic Reasoning Modules for Generalizable Multi-Agent Systems
por: Yao, Bohan, et al.
Publicado: (2025)

Molecular Generative Adversarial Network with Multi-Property Optimization
por: Tang, Huidong, et al.
Publicado: (2024)

GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models
por: Tang, Xiaohang, et al.
Publicado: (2026)

Evaluating Long-Context Reasoning in LLM-Based WebAgents
por: Chung, Andy, et al.
Publicado: (2025)

COMET: Benchmark for Comprehensive Biological Multi-omics Evaluation Tasks and Language Models
por: Ren, Yuchen, et al.
Publicado: (2024)

Graph and Simplicial Complex Prediction Gaussian Process via the Hodgelet Representations
por: Alain, Mathieu, et al.
Publicado: (2025)

Beyond Distribution Sharpening: The Importance of Task Rewards
por: Mittal, Sarthak, et al.
Publicado: (2026)

MLE-Smith: Scaling MLE Tasks with Automated Multi-Agent Pipeline
por: Qiang, Rushi, et al.
Publicado: (2025)

When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems
por: Wang, Zehao, et al.
Publicado: (2026)

Enhancing Player Enjoyment with a Two-Tier DRL and LLM-Based Agent System for Fighting Games
por: Wang, Shouren, et al.
Publicado: (2025)

Agentic Neural Networks: Self-Evolving Multi-Agent Systems via Textual Backpropagation
por: Ma, Xiaowen, et al.
Publicado: (2025)

Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems
por: Feng, Lang, et al.
Publicado: (2026)

The Behavior Gap: Evaluating Zero-shot LLM Agents in Complex Task-Oriented Dialogs
por: Baidya, Avinash, et al.
Publicado: (2025)

Learning Evolving Latent Strategies for Multi-Agent Language Systems without Model Fine-Tuning
por: Tang, Wenlong
Publicado: (2025)

Rethinking Importance Sampling in LLM Policy Optimization: A Cumulative Token Perspective
por: Zhang, Yuheng, et al.
Publicado: (2026)

MASTEST: A LLM-Based Multi-Agent System For RESTful API Tests
por: Han, Xiaoke, et al.
Publicado: (2025)

AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents
por: Ma, Chang, et al.
Publicado: (2024)

Towards General Computer Control with Hierarchical Agents and Multi-Level Action Spaces
por: Dong, Zihan, et al.
Publicado: (2025)

AdamS: Momentum Itself Can Be A Normalizer for LLM Pretraining and Post-training
por: Zhang, Huishuai, et al.
Publicado: (2025)

Evaluation and Benchmarking of LLM Agents: A Survey
por: Mohammadi, Mahmoud, et al.
Publicado: (2025)

AgenticPay: A Multi-Agent LLM Negotiation System for Buyer-Seller Transactions
por: Liu, Xianyang, et al.
Publicado: (2026)

Reliable Self-Harm Risk Screening via Adaptive Multi-Agent LLM Systems
por: Karnam, Meghana, et al.
Publicado: (2026)

On the Trainability of Masked Diffusion Language Models via Blockwise Locality
por: Wang, Yuxiang, et al.
Publicado: (2026)

ComplexityNet: Increasing LLM Inference Efficiency by Learning Task Complexity
por: Bae, Henry, et al.
Publicado: (2023)

CoPS: Empowering LLM Agents with Provable Cross-Task Experience Sharing
por: Yang, Chen, et al.
Publicado: (2024)

Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems
por: Yang, Jiaxi, et al.
Publicado: (2025)

Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
por: Cherepanov, Egor, et al.
Publicado: (2024)

One-step Structure Prediction and Screening for Protein-Ligand Complexes using Multi-Task Geometric Deep Learning
por: He, Kelei, et al.
Publicado: (2024)

GoAgent: Group-of-Agents Communication Topology Generation for LLM-based Multi-Agent Systems
por: Chen, Hongjiang, et al.
Publicado: (2026)