Do Large Language Models Truly Understand Geometric Structures?
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Xiaofeng, Wang, Yiming, Zhu, Wenhong, Wang, Rui |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Do Large Language Models Truly Understand Cross-cultural Differences?
by: Guo, Shiwei, et al.
Published: (2025)
by: Guo, Shiwei, et al.
Published: (2025)
Adding Alignment Control to Language Models
by: Zhu, Wenhong, et al.
Published: (2025)
by: Zhu, Wenhong, et al.
Published: (2025)
Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model
by: Zhu, Wenhong, et al.
Published: (2024)
by: Zhu, Wenhong, et al.
Published: (2024)
Is Self-knowledge and Action Consistent or Not: Investigating Large Language Model's Personality
by: Ai, Yiming, et al.
Published: (2024)
by: Ai, Yiming, et al.
Published: (2024)
MrRoPE: Mixed-radix Rotary Position Embedding
by: Tian, Qingyuan, et al.
Published: (2026)
by: Tian, Qingyuan, et al.
Published: (2026)
Debt Collection Negotiations with Large Language Models: An Evaluation System and Optimizing Decision Making with Multi-Agent
by: Wang, Xiaofeng, et al.
Published: (2025)
by: Wang, Xiaofeng, et al.
Published: (2025)
Flexible Realignment of Language Models
by: Zhu, Wenhong, et al.
Published: (2025)
by: Zhu, Wenhong, et al.
Published: (2025)
Do Large Language Models Truly Grasp Mathematics? An Empirical Exploration From Cognitive Psychology
by: Xie, Wei, et al.
Published: (2024)
by: Xie, Wei, et al.
Published: (2024)
How Well Do Large Language Models Truly Ground?
by: Lee, Hyunji, et al.
Published: (2023)
by: Lee, Hyunji, et al.
Published: (2023)
Improving Open-Ended Text Generation via Adaptive Decoding
by: Zhu, Wenhong, et al.
Published: (2024)
by: Zhu, Wenhong, et al.
Published: (2024)
Cause and Effect: Can Large Language Models Truly Understand Causality?
by: Ashwani, Swagata, et al.
Published: (2024)
by: Ashwani, Swagata, et al.
Published: (2024)
CLEAN-EVAL: Clean Evaluation on Contaminated Large Language Models
by: Zhu, Wenhong, et al.
Published: (2023)
by: Zhu, Wenhong, et al.
Published: (2023)
Optimizing Psychological Counseling with Instruction-Tuned Large Language Models
by: Li, Wenjie, et al.
Published: (2024)
by: Li, Wenjie, et al.
Published: (2024)
Meta-Reasoning: Semantics-Symbol Deconstruction for Large Language Models
by: Wang, Yiming, et al.
Published: (2023)
by: Wang, Yiming, et al.
Published: (2023)
Do Vision-Language Models Truly Perform Vision Reasoning? A Rigorous Study of the Modality Gap
by: Xu, Yige, et al.
Published: (2026)
by: Xu, Yige, et al.
Published: (2026)
Do Large Language Models Understand Logic or Just Mimick Context?
by: Yan, Junbing, et al.
Published: (2024)
by: Yan, Junbing, et al.
Published: (2024)
Do Large Language Models Truly Grasp Addition? A Rule-Focused Diagnostic Using Two-Integer Arithmetic
by: Yan, Yang, et al.
Published: (2025)
by: Yan, Yang, et al.
Published: (2025)
Are Large Language Models Truly Smarter Than Humans?
by: M, Eshwar Reddy, et al.
Published: (2026)
by: M, Eshwar Reddy, et al.
Published: (2026)
Memorization $\neq$ Understanding: Do Large Language Models Have the Ability of Scenario Cognition?
by: Ma, Boxiang, et al.
Published: (2025)
by: Ma, Boxiang, et al.
Published: (2025)
Burn After Reading: Do Multimodal Large Language Models Truly Capture Order of Events in Image Sequences?
by: Song, Yingjin, et al.
Published: (2025)
by: Song, Yingjin, et al.
Published: (2025)
Hybrid Policy Distillation for LLMs
by: Zhu, Wenhong, et al.
Published: (2026)
by: Zhu, Wenhong, et al.
Published: (2026)
How Do Language Models Understand Tables? A Mechanistic Analysis of Cell Location
by: Zhang, Xuanliang, et al.
Published: (2026)
by: Zhang, Xuanliang, et al.
Published: (2026)
Do as We Do, Not as You Think: the Conformity of Large Language Models
by: Weng, Zhiyuan, et al.
Published: (2025)
by: Weng, Zhiyuan, et al.
Published: (2025)
The End of Manual Decoding: Towards Truly End-to-End Language Models
by: Wang, Zhichao, et al.
Published: (2025)
by: Wang, Zhichao, et al.
Published: (2025)
MlingConf: A Comprehensive Study of Multilingual Confidence Estimation on Large Language Models
by: Xue, Boyang, et al.
Published: (2024)
by: Xue, Boyang, et al.
Published: (2024)
CellVerse: Do Large Language Models Really Understand Cell Biology?
by: Zhang, Fan, et al.
Published: (2025)
by: Zhang, Fan, et al.
Published: (2025)
MlingConf: A Comprehensive Study of Multilingual Confidence Estimation on Large Language Models
by: Xue, Boyang, et al.
Published: (2024)
by: Xue, Boyang, et al.
Published: (2024)
Do Large Language Models Understand Morality Across Cultures?
by: Mohammadi, Hadi, et al.
Published: (2025)
by: Mohammadi, Hadi, et al.
Published: (2025)
Lossless Acceleration of Large Language Model via Adaptive N-gram Parallel Decoding
by: Ou, Jie, et al.
Published: (2024)
by: Ou, Jie, et al.
Published: (2024)
Do Multimodal Large Language Models Understand Welding?
by: Khvatskii, Grigorii, et al.
Published: (2025)
by: Khvatskii, Grigorii, et al.
Published: (2025)
ChatASU: Evoking LLM's Reflexion to Truly Understand Aspect Sentiment in Dialogues
by: Liu, Yiding, et al.
Published: (2024)
by: Liu, Yiding, et al.
Published: (2024)
Do Large Language Models Understand Word Senses?
by: Meconi, Domenico, et al.
Published: (2025)
by: Meconi, Domenico, et al.
Published: (2025)
ChartHal: A Fine-grained Framework Evaluating Hallucination of Large Vision Language Models in Chart Understanding
by: Wang, Xingqi, et al.
Published: (2025)
by: Wang, Xingqi, et al.
Published: (2025)
StringLLM: Understanding the String Processing Capability of Large Language Models
by: Wang, Xilong, et al.
Published: (2024)
by: Wang, Xilong, et al.
Published: (2024)
SportQA: A Benchmark for Sports Understanding in Large Language Models
by: Xia, Haotian, et al.
Published: (2024)
by: Xia, Haotian, et al.
Published: (2024)
L-CiteEval: Do Long-Context Models Truly Leverage Context for Responding?
by: Tang, Zecheng, et al.
Published: (2024)
by: Tang, Zecheng, et al.
Published: (2024)
Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models
by: Cheng, Sitao, et al.
Published: (2024)
by: Cheng, Sitao, et al.
Published: (2024)
Do LLMs Truly Understand When a Precedent Is Overruled?
by: Zhang, Li, et al.
Published: (2025)
by: Zhang, Li, et al.
Published: (2025)
SciGPT: A Large Language Model for Scientific Literature Understanding and Knowledge Discovery
by: She, Fengyu, et al.
Published: (2025)
by: She, Fengyu, et al.
Published: (2025)
Metacognitive Prompting Improves Understanding in Large Language Models
by: Wang, Yuqing, et al.
Published: (2023)
by: Wang, Yuqing, et al.
Published: (2023)
Similar Items
-
Do Large Language Models Truly Understand Cross-cultural Differences?
by: Guo, Shiwei, et al.
Published: (2025) -
Adding Alignment Control to Language Models
by: Zhu, Wenhong, et al.
Published: (2025) -
Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model
by: Zhu, Wenhong, et al.
Published: (2024) -
Is Self-knowledge and Action Consistent or Not: Investigating Large Language Model's Personality
by: Ai, Yiming, et al.
Published: (2024) -
MrRoPE: Mixed-radix Rotary Position Embedding
by: Tian, Qingyuan, et al.
Published: (2026)