Do Large Language Models Understand Logic or Just Mimick Context?
Fuente:
arXiv
Saved in:
| Main Authors: | Yan, Junbing, Wang, Chengyu, Huang, Jun, Zhang, Wei |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
EasyDistill: A Comprehensive Toolkit for Effective Knowledge Distillation of Large Language Models
by: Wang, Chengyu, et al.
Published: (2025)
by: Wang, Chengyu, et al.
Published: (2025)
Reasoning with OmniThought: A Large CoT Dataset with Verbosity and Cognitive Difficulty Annotations
by: Cai, Wenrui, et al.
Published: (2025)
by: Cai, Wenrui, et al.
Published: (2025)
Thinking with DistilQwen: A Tale of Four Distilled Reasoning and Reward Model Series
by: Cai, Wenrui, et al.
Published: (2025)
by: Cai, Wenrui, et al.
Published: (2025)
Enhancing Reasoning Abilities of Small LLMs with Cognitive Alignment
by: Cai, Wenrui, et al.
Published: (2025)
by: Cai, Wenrui, et al.
Published: (2025)
Do Large Language Models Excel in Complex Logical Reasoning with Formal Language?
by: Jiang, Jin, et al.
Published: (2025)
by: Jiang, Jin, et al.
Published: (2025)
From Correction to Mastery: Reinforced Distillation of Large Language Model Agents
by: Lyu, Yuanjie, et al.
Published: (2025)
by: Lyu, Yuanjie, et al.
Published: (2025)
CNNSum: Exploring Long-Context Summarization with Large Language Models in Chinese Novels
by: Wei, Lingxiao, et al.
Published: (2024)
by: Wei, Lingxiao, et al.
Published: (2024)
Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning
by: Wang, Jianing, et al.
Published: (2023)
by: Wang, Jianing, et al.
Published: (2023)
DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models
by: Wang, Chengyu, et al.
Published: (2025)
by: Wang, Chengyu, et al.
Published: (2025)
CLOMO: Counterfactual Logical Modification with Large Language Models
by: Huang, Yinya, et al.
Published: (2023)
by: Huang, Yinya, et al.
Published: (2023)
Do Influence Functions Work on Large Language Models?
by: Li, Zhe, et al.
Published: (2024)
by: Li, Zhe, et al.
Published: (2024)
Reason from Fallacy: Enhancing Large Language Models' Logical Reasoning through Logical Fallacy Understanding
by: Li, Yanda, et al.
Published: (2024)
by: Li, Yanda, et al.
Published: (2024)
An Information-Theoretic Framework for Robust Large Language Model Editing
by: Chen, Qizhou, et al.
Published: (2025)
by: Chen, Qizhou, et al.
Published: (2025)
Do Large Language Models Understand Word Senses?
by: Meconi, Domenico, et al.
Published: (2025)
by: Meconi, Domenico, et al.
Published: (2025)
JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models
by: Chen, Michael K., et al.
Published: (2025)
by: Chen, Michael K., et al.
Published: (2025)
KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion
by: Wei, Yanbin, et al.
Published: (2024)
by: Wei, Yanbin, et al.
Published: (2024)
Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities
by: Hua, Wenyue, et al.
Published: (2024)
by: Hua, Wenyue, et al.
Published: (2024)
A Short Survey on Small Reasoning Models: Training, Inference, Applications and Research Directions
by: Wang, Chengyu, et al.
Published: (2025)
by: Wang, Chengyu, et al.
Published: (2025)
Understanding the Dilemma of Unlearning for Large Language Models
by: Zhang, Qingjie, et al.
Published: (2025)
by: Zhang, Qingjie, et al.
Published: (2025)
LooGLE: Can Long-Context Language Models Understand Long Contexts?
by: Li, Jiaqi, et al.
Published: (2023)
by: Li, Jiaqi, et al.
Published: (2023)
Natural Context Drift Undermines the Natural Language Understanding of Large Language Models
by: Wu, Yulong, et al.
Published: (2025)
by: Wu, Yulong, et al.
Published: (2025)
DAM: Dynamic Attention Mask for Long-Context Large Language Model Inference Acceleration
by: Zhang, Hanzhi, et al.
Published: (2025)
by: Zhang, Hanzhi, et al.
Published: (2025)
Do They Understand Them? An Updated Evaluation on Nonbinary Pronoun Handling in Large Language Models
by: Tang, Xushuo, et al.
Published: (2025)
by: Tang, Xushuo, et al.
Published: (2025)
Towards Context-Invariant Safety Alignment for Large Language Models
by: Wang, Yixu, et al.
Published: (2026)
by: Wang, Yixu, et al.
Published: (2026)
Evaluating the Translation Performance of Large Language Models Based on Euas-20
by: Huang, Yan, et al.
Published: (2024)
by: Huang, Yan, et al.
Published: (2024)
Logical Reasoning in Large Language Models: A Survey
by: Liu, Hanmeng, et al.
Published: (2025)
by: Liu, Hanmeng, et al.
Published: (2025)
Just Go Parallel: Improving the Multilingual Capabilities of Large Language Models
by: Qorib, Muhammad Reza, et al.
Published: (2025)
by: Qorib, Muhammad Reza, et al.
Published: (2025)
Logic Contrastive Reasoning with Lightweight Large Language Model for Math Word Problems
by: Kai, Ding, et al.
Published: (2024)
by: Kai, Ding, et al.
Published: (2024)
MMRAG: Multi-Mode Retrieval-Augmented Generation with Large Language Models for Biomedical In-Context Learning
by: Zhan, Zaifu, et al.
Published: (2025)
by: Zhan, Zaifu, et al.
Published: (2025)
Large Language Models are In-Context Molecule Learners
by: Li, Jiatong, et al.
Published: (2024)
by: Li, Jiatong, et al.
Published: (2024)
LongSafety: Evaluating Long-Context Safety of Large Language Models
by: Lu, Yida, et al.
Published: (2025)
by: Lu, Yida, et al.
Published: (2025)
PSC: Extending Context Window of Large Language Models via Phase Shift Calibration
by: Zhu, Wenqiao, et al.
Published: (2025)
by: Zhu, Wenqiao, et al.
Published: (2025)
Do Large Language Models Possess Sensitive to Sentiment?
by: Liu, Yang, et al.
Published: (2024)
by: Liu, Yang, et al.
Published: (2024)
Assessing and Understanding Creativity in Large Language Models
by: Zhao, Yunpu, et al.
Published: (2024)
by: Zhao, Yunpu, et al.
Published: (2024)
LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models
by: Gui, Jiayi, et al.
Published: (2024)
by: Gui, Jiayi, et al.
Published: (2024)
Emergent Structured Representations Support Flexible In-Context Inference in Large Language Models
by: Xu, Ningyu, et al.
Published: (2026)
by: Xu, Ningyu, et al.
Published: (2026)
Do Large Language Models Mirror Cognitive Language Processing?
by: Ren, Yuqi, et al.
Published: (2024)
by: Ren, Yuqi, et al.
Published: (2024)
GLoRE: Evaluating Logical Reasoning of Large Language Models
by: liu, Hanmeng, et al.
Published: (2023)
by: liu, Hanmeng, et al.
Published: (2023)
Mimicking or Reasoning: Rethinking Multi-Modal In-Context Learning in Vision-Language Models
by: Huang, Chengyue, et al.
Published: (2025)
by: Huang, Chengyue, et al.
Published: (2025)
Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond
by: Xu, Fangzhi, et al.
Published: (2023)
by: Xu, Fangzhi, et al.
Published: (2023)
Similar Items
-
EasyDistill: A Comprehensive Toolkit for Effective Knowledge Distillation of Large Language Models
by: Wang, Chengyu, et al.
Published: (2025) -
Reasoning with OmniThought: A Large CoT Dataset with Verbosity and Cognitive Difficulty Annotations
by: Cai, Wenrui, et al.
Published: (2025) -
Thinking with DistilQwen: A Tale of Four Distilled Reasoning and Reward Model Series
by: Cai, Wenrui, et al.
Published: (2025) -
Enhancing Reasoning Abilities of Small LLMs with Cognitive Alignment
by: Cai, Wenrui, et al.
Published: (2025) -
Do Large Language Models Excel in Complex Logical Reasoning with Formal Language?
by: Jiang, Jin, et al.
Published: (2025)