:: Library Catalog

Buchumschlag

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Ahmad, Zishan, Gopalakrishnan, Saisubramaniam
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Computation and Language Artificial Intelligence
Online-Zugang:	https://arxiv.org/abs/2509.22224
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Leveraging Knowledge Graphs and LLM Reasoning to Identify Operational Bottlenecks for Warehouse Planning Assistance
von: Parekh, Rishi, et al.
Veröffentlicht: (2025)

Intelligent Human-Machine Partnership for Manufacturing: Enhancing Warehouse Planning through Simulation-Driven Knowledge Graphs and LLM Collaboration
von: Thogaru, Himabindu, et al.
Veröffentlicht: (2025)

InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models
von: Yan, Yuchen, et al.
Veröffentlicht: (2025)

MixReasoning: Switching Modes to Think
von: Lu, Haiquan, et al.
Veröffentlicht: (2025)

DynamicMind: A Tri-Mode Thinking System for Large Language Models
von: Li, Wei, et al.
Veröffentlicht: (2025)

Surrogate-Guided Quantum Discovery in Black-Box Landscapes with Latent-Quadratic Interaction Embedding Transformers
von: Gopalakrishnan, Saisubramaniam, et al.
Veröffentlicht: (2026)

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

Think$^{2}$: Grounded Metacognitive Reasoning in Large Language Models
von: Elenjical, Abraham Paul, et al.
Veröffentlicht: (2026)

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning
von: Cheng, Xiaoxue, et al.
Veröffentlicht: (2025)

Modeling Hierarchical Thinking in Large Reasoning Models
von: Shahariar, G M, et al.
Veröffentlicht: (2025)

An Empirical Study of Many-to-Many Summarization with Large Language Models
von: Wang, Jiaan, et al.
Veröffentlicht: (2025)

To Think or Not To Think, That is The Question for Large Reasoning Models in Theory of Mind Tasks
von: Gong, Nanxu, et al.
Veröffentlicht: (2026)

Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding
von: Liu, Tianqiao, et al.
Veröffentlicht: (2024)

Thinking About Thinking: Evaluating Reasoning in Post-Trained Language Models
von: Singla, Pratham, et al.
Veröffentlicht: (2025)

Certainty-Guided Reasoning in Large Language Models: A Dynamic Thinking Budget Approach
von: Nogueira, João Paulo, et al.
Veröffentlicht: (2025)

Exploring the Compositional Deficiency of Large Language Models in Mathematical Reasoning
von: Zhao, Jun, et al.
Veröffentlicht: (2024)

To Think or Not to Think: Exploring the Unthinking Vulnerability in Large Reasoning Models
von: Zhu, Zihao, et al.
Veröffentlicht: (2025)

InvThink: Premortem Reasoning for Safer Language Models
von: Kim, Yubin, et al.
Veröffentlicht: (2025)

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

Benchmarking the Thinking Mode of Multimodal Large Language Models in Clinical Tasks
von: Hong, Jindong, et al.
Veröffentlicht: (2025)

Reasoning Beyond Chain-of-Thought: A Latent Computational Mode in Large Language Models
von: He, Zhenghao, et al.
Veröffentlicht: (2026)

AdapThink: Adaptive Thinking Preferences for Reasoning Language Model
von: Wan, Xu, et al.
Veröffentlicht: (2025)

Exploring the System 1 Thinking Capability of Large Reasoning Models
von: Zhang, Wenyuan, et al.
Veröffentlicht: (2025)

Fast-Slow Thinking GRPO for Large Vision-Language Model Reasoning
von: Xiao, Wenyi, et al.
Veröffentlicht: (2025)

Causality extraction from medical text using Large Language Models (LLMs)
von: Gopalakrishnan, Seethalakshmi, et al.
Veröffentlicht: (2024)

EXAONE 4.0: Unified Large Language Models Integrating Non-reasoning and Reasoning Modes
von: Bae, Kyunghoon, et al.
Veröffentlicht: (2025)

How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition
von: Dong, Guanting, et al.
Veröffentlicht: (2023)

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey
von: Zhu, Jason, et al.
Veröffentlicht: (2025)

Evaluating the Limits of Large Language Models in Multilingual Legal Reasoning
von: Ioannou, Antreas, et al.
Veröffentlicht: (2025)

CHATATC: Large Language Model-Driven Conversational Agents for Supporting Strategic Air Traffic Flow Management
von: Abdulhak, Sinan, et al.
Veröffentlicht: (2024)

Focused Large Language Models are Stable Many-Shot Learners
von: Yuan, Peiwen, et al.
Veröffentlicht: (2024)

Limitations of Large Language Models in Clinical Problem-Solving Arising from Inflexible Reasoning
von: Kim, Jonathan, et al.
Veröffentlicht: (2025)

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning
von: Zhu, Rongzhi, et al.
Veröffentlicht: (2025)

What Really Controls Temporal Reasoning in Large Language Models: Tokenisation or Representation of Time?
von: Bhatia, Gagan, et al.
Veröffentlicht: (2026)

Cross-lingual Collapse: How Language-Centric Foundation Models Shape Reasoning in Large Language Models
von: Park, Cheonbok, et al.
Veröffentlicht: (2025)

Dynamic Thinking-Token Selection for Efficient Reasoning in Large Reasoning Models
von: Guo, Zhenyuan, et al.
Veröffentlicht: (2026)

Reasoning Factual Knowledge in Structured Data with Large Language Models
von: Huang, Sirui, et al.
Veröffentlicht: (2024)

Speculative Thinking: Enhancing Small-Model Reasoning with Large Model Guidance at Inference Time
von: Yang, Wang, et al.
Veröffentlicht: (2025)

Controlling Thinking Speed in Reasoning Models
von: Lin, Zhengkai, et al.
Veröffentlicht: (2025)

Cognitive Decision Routing in Large Language Models: When to Think Fast, When to Think Slow
von: Du, Y., et al.
Veröffentlicht: (2025)