Probing the "Psyche'' of Large Reasoning Models: Understanding Through a Human Lens
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Yuxiang, Wu, Zuohan, Wang, Ziwei, Yu, Xiangning, Li, Xujia, Yang, Linyi, Yang, Mengyue, Wang, Jun, Chen, Lei |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning
by: Yu, Xiangning, et al.
Published: (2025)
by: Yu, Xiangning, et al.
Published: (2025)
Delusions of Large Language Models
by: Xu, Hongshen, et al.
Published: (2025)
by: Xu, Hongshen, et al.
Published: (2025)
How Likely Do LLMs with CoT Mimic Human Reasoning?
by: Bao, Guangsheng, et al.
Published: (2024)
by: Bao, Guangsheng, et al.
Published: (2024)
CulturePark: Boosting Cross-cultural Understanding in Large Language Models
by: Li, Cheng, et al.
Published: (2024)
by: Li, Cheng, et al.
Published: (2024)
CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges
by: Wang, Zi-Han, et al.
Published: (2026)
by: Wang, Zi-Han, et al.
Published: (2026)
OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models
by: Wang, Jun, et al.
Published: (2024)
by: Wang, Jun, et al.
Published: (2024)
PSSD: Making Large Language Models Self-denial via Human Psyche Structure
by: Liao, Jinzhi, et al.
Published: (2025)
by: Liao, Jinzhi, et al.
Published: (2025)
Direct Value Optimization: Improving Chain-of-Thought Reasoning in LLMs with Refined Values
by: Zhang, Hongbo, et al.
Published: (2025)
by: Zhang, Hongbo, et al.
Published: (2025)
Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration
by: Yao, Bingsheng, et al.
Published: (2025)
by: Yao, Bingsheng, et al.
Published: (2025)
From Prediction to Justification: Aligning Sentiment Reasoning with Human Rationale via Reinforcement Learning
by: Zhang, Shihao, et al.
Published: (2026)
by: Zhang, Shihao, et al.
Published: (2026)
PsychCounsel-Bench: Evaluating the Psychology Intelligence of Large Language Models
by: Zeng, Min
Published: (2025)
by: Zeng, Min
Published: (2025)
CultureScope: A Dimensional Lens for Probing Cultural Understanding in LLMs
by: Zhang, Jinghao, et al.
Published: (2025)
by: Zhang, Jinghao, et al.
Published: (2025)
A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models
by: Zheng, Congmin, et al.
Published: (2025)
by: Zheng, Congmin, et al.
Published: (2025)
From Human Cognition to Neural Activations: Probing the Computational Primitives of Spatial Reasoning in LLMs
by: An, Jiyuan, et al.
Published: (2026)
by: An, Jiyuan, et al.
Published: (2026)
Induction Head Toxicity Mechanistically Explains Repetition Curse in Large Language Models
by: Wang, Shuxun, et al.
Published: (2025)
by: Wang, Shuxun, et al.
Published: (2025)
A Cognitive Evaluation Benchmark of Image Reasoning and Description for Large Vision-Language Models
by: Song, Xiujie, et al.
Published: (2024)
by: Song, Xiujie, et al.
Published: (2024)
Evaluation of data inconsistency for multi-modal sentiment analysis
by: Wang, Yufei, et al.
Published: (2024)
by: Wang, Yufei, et al.
Published: (2024)
A Survey on Evaluation of Large Language Models
by: Chang, Yupeng, et al.
Published: (2023)
by: Chang, Yupeng, et al.
Published: (2023)
An Empirical Analysis of Uncertainty in Large Language Model Evaluations
by: Xie, Qiujie, et al.
Published: (2025)
by: Xie, Qiujie, et al.
Published: (2025)
TabularMath: Understanding Math Reasoning over Tables with Large Language Models
by: Tian, Shi-Yu, et al.
Published: (2025)
by: Tian, Shi-Yu, et al.
Published: (2025)
Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation
by: Wang, Xinyi, et al.
Published: (2024)
by: Wang, Xinyi, et al.
Published: (2024)
Supervised Knowledge Makes Large Language Models Better In-context Learners
by: Yang, Linyi, et al.
Published: (2023)
by: Yang, Linyi, et al.
Published: (2023)
Efficient Prompt Optimization Through the Lens of Best Arm Identification
by: Shi, Chengshuai, et al.
Published: (2024)
by: Shi, Chengshuai, et al.
Published: (2024)
PsychBench: A comprehensive and professional benchmark for evaluating the performance of LLM-assisted psychiatric clinical practice
by: Liu, Shuyu, et al.
Published: (2025)
by: Liu, Shuyu, et al.
Published: (2025)
Understanding Moral Reasoning Trajectories in Large Language Models: Toward Probing-Based Explainability
by: Huang, Fan, et al.
Published: (2026)
by: Huang, Fan, et al.
Published: (2026)
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)
MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Framework
by: Mi, Qirui, et al.
Published: (2025)
by: Mi, Qirui, et al.
Published: (2025)
Fine-Grained Interpretation of Political Opinions in Large Language Models
by: Hu, Jingyu, et al.
Published: (2025)
by: Hu, Jingyu, et al.
Published: (2025)
Large Language Models Are Neurosymbolic Reasoners
by: Fang, Meng, et al.
Published: (2024)
by: Fang, Meng, et al.
Published: (2024)
Can Large Language Models Replace Data Scientists in Biomedical Research?
by: Wang, Zifeng, et al.
Published: (2024)
by: Wang, Zifeng, et al.
Published: (2024)
Error as a Lens: Probing LLM Reasoning through Synthetic Misconception Generation
by: Yang, Xinming, et al.
Published: (2026)
by: Yang, Xinming, et al.
Published: (2026)
Efficient Reasoning Through Suppression of Self-Affirmation Reflections in Large Reasoning Models
by: Liu, Kaiyuan, et al.
Published: (2025)
by: Liu, Kaiyuan, et al.
Published: (2025)
Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning
by: Zhang, Xinlu, et al.
Published: (2024)
by: Zhang, Xinlu, et al.
Published: (2024)
AdamMeme: Adaptively Probe the Reasoning Capacity of Multimodal Large Language Models on Harmfulness
by: Chen, Zixin, et al.
Published: (2025)
by: Chen, Zixin, et al.
Published: (2025)
Scientists' First Exam: Probing Cognitive Abilities of MLLM via Perception, Understanding, and Reasoning
by: Zhou, Yuhao, et al.
Published: (2025)
by: Zhou, Yuhao, et al.
Published: (2025)
CodeMind: Evaluating Large Language Models for Code Reasoning
by: Liu, Changshu, et al.
Published: (2024)
by: Liu, Changshu, et al.
Published: (2024)
A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document Understanding
by: Lu, Jinghui, et al.
Published: (2024)
by: Lu, Jinghui, et al.
Published: (2024)
NUMCoT: Numerals and Units of Measurement in Chain-of-Thought Reasoning using Large Language Models
by: Xu, Ancheng, et al.
Published: (2024)
by: Xu, Ancheng, et al.
Published: (2024)
Reasoning or Retrieval? A Study of Answer Attribution on Large Reasoning Models
by: Wang, Yuhui, et al.
Published: (2025)
by: Wang, Yuhui, et al.
Published: (2025)
A Survey on Large Language Models for Mathematical Reasoning
by: Wang, Peng-Yuan, et al.
Published: (2025)
by: Wang, Peng-Yuan, et al.
Published: (2025)
Similar Items
-
Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning
by: Yu, Xiangning, et al.
Published: (2025) -
Delusions of Large Language Models
by: Xu, Hongshen, et al.
Published: (2025) -
How Likely Do LLMs with CoT Mimic Human Reasoning?
by: Bao, Guangsheng, et al.
Published: (2024) -
CulturePark: Boosting Cross-cultural Understanding in Large Language Models
by: Li, Cheng, et al.
Published: (2024) -
CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges
by: Wang, Zi-Han, et al.
Published: (2026)