:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ning, Yansong, Liu, Mianpeng, Ye, Jingwen, Zhang, Weidong, Liu, Hao
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence
Online Access:	https://arxiv.org/abs/2605.28398
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

USTBench: Benchmarking and Dissecting Spatiotemporal Reasoning of LLMs as Urban Agents
by: Lai, Siqi, et al.
Published: (2025)

When to Continue Thinking: Adaptive Thinking Mode Switching for Efficient Reasoning
by: Zhang, Xiaoyun, et al.
Published: (2025)

MixReasoning: Switching Modes to Think
by: Lu, Haiquan, et al.
Published: (2025)

UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction
by: Ning, Yansong, et al.
Published: (2024)

Strategy-Aware Optimization Modeling with Reasoning LLMs
by: Zhao, Ruiqing, et al.
Published: (2026)

Demystifying Hybrid Thinking: Can LLMs Truly Switch Between Think and No-Think?
by: Wang, Shouren, et al.
Published: (2025)

OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation
by: Zhang, Shengjia, et al.
Published: (2025)

AgentBalance: Backbone-then-Topology Design for Cost-Effective Multi-Agent Systems under Budget Constraints
by: Cai, Shuowei, et al.
Published: (2025)

Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data
by: Liu, Xiao, et al.
Published: (2024)

SwiReasoning: Switch-Thinking in Latent and Explicit for Pareto-Superior Reasoning LLMs
by: Shi, Dachuan, et al.
Published: (2025)

Not All Thoughts are Generated Equal: Efficient LLM Reasoning via Multi-Turn Reinforcement Learning
by: Ning, Yansong, et al.
Published: (2025)

MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs
by: Zeng, Zhongshen, et al.
Published: (2024)

Agent-Omit: Adaptive Context Omission for Efficient LLM Agents
by: Ning, Yansong, et al.
Published: (2026)

Self-Route: Automatic Mode Switching via Capability Estimation for Efficient Reasoning
by: He, Yang, et al.
Published: (2025)

TrafficClaw: A Generalizable LLM Agent in the Unified Physical Environment for Urban Traffic Control
by: Lai, Siqi, et al.
Published: (2026)

Adaptive Dual Reasoner: Large Reasoning Models Can Think Efficiently by Hybrid Reasoning
by: Zhang, Yujian, et al.
Published: (2025)

Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs
by: Yang, Dayu, et al.
Published: (2025)

Thinking-Based Non-Thinking: Solving the Reward Hacking Problem in Training Hybrid Reasoning Models via Reinforcement Learning
by: Gan, Siyuan, et al.
Published: (2026)

Plan before Solving: Problem-Aware Strategy Routing for Mathematical Reasoning with LLMs
by: Qi, Shihao, et al.
Published: (2025)

The Zero-Step Thinking: An Empirical Study of Mode Selection as Harder Early Exit in Reasoning Models
by: Tan, Yuqiao, et al.
Published: (2025)

Understanding Mode Switching in Human-AI Collaboration: Behavioral Insights and Predictive Modeling
by: Nargund, Avinash Ajit, et al.
Published: (2025)

How Do Answer Tokens Read Reasoning Traces? Self-Reading Patterns in Thinking LLMs for Quantitative Reasoning
by: Chen, Haoyang, et al.
Published: (2026)

Benchmarking MLLM-based Web Understanding: Reasoning, Robustness and Safety
by: Liu, Junliang, et al.
Published: (2025)

An Empirical Study of Reasoning Steps in Thinking Code LLMs
by: Xue, Haoran, et al.
Published: (2025)

Benchmarking Multimodal LLMs on Recognition and Understanding over Chemical Tables
by: Zhou, Yitong, et al.
Published: (2025)

Thinking in Text and Images: Interleaved Vision--Language Reasoning Traces for Long-Horizon Robot Manipulation
by: Liu, Jinkun, et al.
Published: (2026)

Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models
by: Liu, Yongjiang, et al.
Published: (2025)

AraTable: Benchmarking LLMs' Reasoning and Understanding of Arabic Tabular Data
by: Alshaikh, Rana, et al.
Published: (2025)

DAST: Difficulty-Adaptive Slow-Thinking for Large Reasoning Models
by: Shen, Yi, et al.
Published: (2025)

Understanding the Role of LLMs in Multimodal Evaluation Benchmarks
by: Jiang, Botian, et al.
Published: (2024)

Understanding Financial Reasoning in AI: A Multimodal Benchmark and Error Learning Approach
by: Deng, Shuangyan, et al.
Published: (2025)

Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
by: Zhou, Yitong, et al.
Published: (2025)

DeepThink3D: Enhancing Large Language Models with Programmatic Reasoning in Complex 3D Situated Reasoning Tasks
by: Song, Jiayi, et al.
Published: (2025)

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs
by: Xu, Zhao, et al.
Published: (2024)

Path-Lock Expert: Separating Reasoning Mode in Hybrid Thinking via Architecture-Level Separation
by: Wang, Shouren, et al.
Published: (2026)

RefTool: Reference-Guided Tool Creation for Knowledge-Intensive Reasoning
by: Liu, Xiao, et al.
Published: (2025)

MedThink: Enhancing Diagnostic Accuracy in Small Models via Teacher-Guided Reasoning Correction
by: Su, Xinchun, et al.
Published: (2026)

MMLU-Reason: Benchmarking Multi-Task Multi-modal Language Understanding and Reasoning
by: Tie, Guiyao, et al.
Published: (2025)

Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications
by: Han, Jindong, et al.
Published: (2025)

CircuitSeer: Mining High-Quality Data by Probing Mathematical Reasoning Circuits in LLMs
by: Wang, Shaobo, et al.
Published: (2025)