Image de couverture de livre

A Comprehensive Evaluation of LLM Reasoning: From Single-Model to Multi-Agent Paradigms

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Li, Yapeng, Yu, Jiakuo, Liu, Zhixin, Liu, Xinnan, Yu, Jing, Li, Songze, Su, Tonghua
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications
par: Zidan, Arif Hassan, et autres
Publié: (2026)

MSfusion: A Dynamic Model Splitting Approach for Resource-Constrained Machines to Collaboratively Train Larger Models
par: Xie, Jin, et autres
Publié: (2024)

Training Task Reasoning LLM Agents for Multi-turn Task Planning via Single-turn Reinforcement Learning
par: Hu, Hanjiang, et autres
Publié: (2025)

Agent-Oriented Planning in Multi-Agent Systems
par: Li, Ao, et autres
Publié: (2024)

FuncPoison: Poisoning Function Library to Hijack Multi-agent Autonomous Driving Systems
par: Long, Yuzhen, et autres
Publié: (2025)

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review
par: Ferrag, Mohamed Amine, et autres
Publié: (2025)

MOSAIC: A Unified Platform for Cross-Paradigm Comparison and Evaluation of Homogeneous and Heterogeneous Multi-Agent RL, LLM, VLM, and Human Decision-Makers
par: Mousa, Abdulhamid M., et autres
Publié: (2026)

OmniLytics+: A Secure, Efficient, and Affordable Blockchain Data Market for Machine Learning through Off-Chain Processing
par: Li, Songze, et autres
Publié: (2024)

Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit
par: Yao, Duanyi, et autres
Publié: (2024)

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games
par: Li, Zhengyang, et autres
Publié: (2025)

TUNI: A Textual Unimodal Detector for Identity Inference in CLIP Models
par: Li, Songze, et autres
Publié: (2024)

From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium
par: Yi, Xie, et autres
Publié: (2025)

ContextEvolve: Multi-Agent Context Compression for Systems Code Optimization
par: Su, Hongyuan, et autres
Publié: (2026)

Knowledge-Driven Multi-Turn Jailbreaking on Large Language Models
par: Li, Songze, et autres
Publié: (2026)

SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks
par: Zhou, Yifei, et autres
Publié: (2025)

Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation
par: Wang, Yuxiang, et autres
Publié: (2025)

A Simple "Try Again" Can Elicit Multi-Turn LLM Reasoning
par: Liu, Licheng, et autres
Publié: (2025)

Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-to-Image Diffusion Models
par: Wang, Kai, et autres
Publié: (2026)

Foundation Models for Scientific Discovery: From Paradigm Enhancement to Paradigm Transition
par: Liu, Fan, et autres
Publié: (2025)

FedMeS: Personalized Federated Continual Learning Leveraging Local Memory
par: Xie, Jin, et autres
Publié: (2024)

From Solo to Symphony: Orchestrating Multi-Agent Collaboration with Single-Agent Demos
par: Wang, Xun, et autres
Publié: (2025)

ASTRA: Adaptive Semantic Tree Reasoning Architecture for Complex Table Question Answering
par: Guo, Xiaoke, et autres
Publié: (2026)

MT2ST: Adaptive Multi-Task to Single-Task Learning
par: Liu, Dong, et autres
Publié: (2024)

Towards Client Driven Federated Learning
par: Li, Songze, et autres
Publié: (2024)

Dive into the Agent Matrix: A Realistic Evaluation of Self-Replication Risk in LLM Agents
par: Zhang, Boxuan, et autres
Publié: (2025)

Time-R1: Towards Comprehensive Temporal Reasoning in LLMs
par: Liu, Zijia, et autres
Publié: (2025)

FloydNet: A Learning Paradigm for Global Relational Reasoning
par: Yu, Jingcheng, et autres
Publié: (2026)

Reason in Chains, Learn in Trees: Self-Rectification and Grafting for Multi-turn Agent Policy Optimization
par: Li, Yu, et autres
Publié: (2026)

LLM Economist: Large Population Models and Mechanism Design in Multi-Agent Generative Simulacra
par: Karten, Seth, et autres
Publié: (2025)

Dependency-based Anomaly Detection: a General Framework and Comprehensive Evaluation
par: Lu, Sha, et autres
Publié: (2020)

GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning
par: Xiang, Zhen, et autres
Publié: (2024)

Scaling Graph Chain-of-Thought Reasoning: A Multi-Agent Framework with Efficient LLM Serving
par: Huan, Chengying, et autres
Publié: (2025)

CoG: Controllable Graph Reasoning via Relational Blueprints and Failure-Aware Refinement over Knowledge Graphs
par: Liu, Yuanxiang, et autres
Publié: (2026)

Odysseus: Jailbreaking Commercial Multimodal LLM-integrated Systems via Dual Steganography
par: Li, Songze, et autres
Publié: (2025)

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents
par: Quarantiello, Luigi, et autres
Publié: (2025)

Evaluating Mathematical Reasoning Across Large Language Models: A Fine-Grained Approach
par: Jahin, Afrar, et autres
Publié: (2025)

MASteer: Multi-Agent Adaptive Steer Strategy for End-to-End LLM Trustworthiness Repair
par: Li, Changqing, et autres
Publié: (2025)

Reinforcing Multi-Turn Reasoning in LLM Agents via Turn-Level Reward Design
par: Wei, Quan, et autres
Publié: (2025)

From Belief Entrenchment to Robust Reasoning in LLM Agents
par: Oh, Jihwan, et autres
Publié: (2025)

How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
par: Dai, Xinnan, et autres
Publié: (2024)