Imagen de Portada

Multi-agent AI systems outperform human teams in creativity

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Hu, Tiancheng, Jiang, Yixuan, Li, Haotian, Hernández-Orallo, José, Xie, Xing, Collier, Nigel, Stillwell, David, Sun, Luning
Formato:	Preprint
Publicado:	2026
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

iNews: A Multimodal Dataset for Modeling Personalized Affective Responses to News
por: Hu, Tiancheng, et al.
Publicado: (2025)

Quantifying the Persona Effect in LLM Simulations
por: Hu, Tiancheng, et al.
Publicado: (2024)

Evaluating General-Purpose AI with Psychometrics
por: Wang, Xiting, et al.
Publicado: (2023)

Navigating the Alignment-Calibration Trade-off: A Pareto-Superior Frontier via Model Merging
por: Hu, Tiancheng, et al.
Publicado: (2025)

Can LLM be a Personalized Judge?
por: Dong, Yijiang River, et al.
Publicado: (2024)

Confident Rankings with Fewer Items: Adaptive LLM Evaluation with Continuous Scores
por: Balkır, Esma, et al.
Publicado: (2026)

Large Language Models show both individual and collective creativity comparable to humans
por: Sun, Luning, et al.
Publicado: (2024)

Steer Model beyond Assistant: Controlling System Prompt Strength via Contrastive Decoding
por: Dong, Yijiang River, et al.
Publicado: (2026)

When Personalization Meets Reality: A Multi-Faceted Analysis of Personalized Preference Learning
por: Dong, Yijiang River, et al.
Publicado: (2025)

A Survey on Prompt Tuning
por: Li, Zongqian, et al.
Publicado: (2025)

PT-MoE: An Efficient Finetuning Framework for Integrating Mixture-of-Experts into Prompt Tuning
por: Li, Zongqian, et al.
Publicado: (2025)

500xCompressor: Generalized Prompt Compression for Large Language Models
por: Li, Zongqian, et al.
Publicado: (2024)

Prompt Compression for Large Language Models: A Survey
por: Li, Zongqian, et al.
Publicado: (2024)

Unlocking Structure Measuring: Introducing PDD, an Automatic Metric for Positional Discourse Coherence
por: Liu, Yinhong, et al.
Publicado: (2024)

Confidence Estimation for LLMs in Multi-turn Interactions
por: Zhang, Caiqi, et al.
Publicado: (2026)

Beyond the Final Layer: Intermediate Representations for Better Multilingual Calibration in Large Language Models
por: Zhou, Ej, et al.
Publicado: (2025)

Measuring Data Science Automation: A Survey of Evaluation Tools for AI Assistants and Agents
por: Testini, Irene, et al.
Publicado: (2025)

Augmenting Rating-Scale Measures with Text-Derived Items Using the Information-Determined Scoring (IDS) Framework
por: Watson, Joe, et al.
Publicado: (2025)

SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors
por: Hu, Tiancheng, et al.
Publicado: (2025)

COFFEE: A Contrastive Oracle-Free Framework for Event Extraction
por: Zhang, Meiru, et al.
Publicado: (2023)

Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization
por: Xing, Tiancheng, et al.
Publicado: (2025)

Value of Information: A Framework for Human-Agent Communication
por: Dong, Yijiang River, et al.
Publicado: (2026)

Generative Language Models Exhibit Social Identity Biases
por: Hu, Tiancheng, et al.
Publicado: (2023)

Flexi-LoRA with Input-Adaptive Ranks: Efficient Finetuning for Speech and Reasoning Tasks
por: Li, Zongqian, et al.
Publicado: (2026)

Time to Revist Exact Match
por: Abbood, Auss, et al.
Publicado: (2025)

Attention Instruction: Amplifying Attention in the Middle via Prompting
por: Zhang, Meiru, et al.
Publicado: (2024)

TOAD: Task-Oriented Automatic Dialogs with Diverse Response Styles
por: Liu, Yinhong, et al.
Publicado: (2024)

Multi-Trigger Poisoning Amplifies Backdoor Vulnerabilities in LLMs
por: Sivapiromrat, Sanhanat, et al.
Publicado: (2025)

Conversational Complexity for Assessing Risk in Large Language Models
por: Burden, John, et al.
Publicado: (2024)

Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models
por: Huang, Yupan, et al.
Publicado: (2023)

General Scales Unlock AI Evaluation with Explanatory and Predictive Power
por: Zhou, Lexin, et al.
Publicado: (2025)

ReasonGraph: Visualisation of Reasoning Paths
por: Li, Zongqian, et al.
Publicado: (2025)

LUQ: Long-text Uncertainty Quantification for LLMs
por: Zhang, Caiqi, et al.
Publicado: (2024)

PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMs
por: Han, Jiuzhou, et al.
Publicado: (2023)

100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances
por: Pacchiardi, Lorenzo, et al.
Publicado: (2024)

Privacy-R1: Privacy-Aware Multi-LLM Agent Collaboration via Reinforcement Learning
por: Hui, Zheng, et al.
Publicado: (2025)

Evolving Diverse Red-team Language Models in Multi-round Multi-agent Games
por: Ma, Chengdong, et al.
Publicado: (2023)

All Roads Lead to Rome: Graph-Based Confidence Estimation for Large Language Model Reasoning
por: Zhang, Caiqi, et al.
Publicado: (2025)

Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers
por: Pacchiardi, Lorenzo, et al.
Publicado: (2024)

Psychometric Personality Shaping Modulates Capabilities and Safety in Language Models
por: Fitz, Stephen, et al.
Publicado: (2025)