A Categorical Analysis of Large Language Models and Why LLMs Circumvent the Symbol Grounding Problem
Fuente:
arXiv
Saved in:
| Main Authors: | Floridi, Luciano, Jia, Yiyang, Tohmé, Fernando |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Conjecture on a Fundamental Trade-Off between Certainty and Scope in Symbolic and Generative AI
by: Floridi, Luciano
Published: (2025)
by: Floridi, Luciano
Published: (2025)
What Kind of Reasoning (if any) is an LLM actually doing? On the Stochastic Nature and Abductive Appearance of Large Language Models
by: Floridi, Luciano, et al.
Published: (2025)
by: Floridi, Luciano, et al.
Published: (2025)
Evaluating Large Language Models on the Frame and Symbol Grounding Problems: A Zero-shot Benchmark
by: Oka, Shoko
Published: (2025)
by: Oka, Shoko
Published: (2025)
The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems
by: Mokander, Jakob, et al.
Published: (2024)
by: Mokander, Jakob, et al.
Published: (2024)
Circumventing Safety Alignment in Large Language Models Through Embedding Space Toxicity Attenuation
by: Zhang, Zhibo, et al.
Published: (2025)
by: Zhang, Zhibo, et al.
Published: (2025)
The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: What can they learn from each other?
by: Mokander, Jakob, et al.
Published: (2024)
by: Mokander, Jakob, et al.
Published: (2024)
Problems With Large Language Models for Learner Modelling: Why LLMs Alone Fall Short for Responsible Tutoring in K--12 Education
by: Hooshyar, Danial, et al.
Published: (2025)
by: Hooshyar, Danial, et al.
Published: (2025)
Exploring Large Language Models for Semantic Analysis and Categorization of Android Malware
by: Walton, Brandon J, et al.
Published: (2025)
by: Walton, Brandon J, et al.
Published: (2025)
ISR: Invertible Symbolic Regression
by: Tohme, Tony, et al.
Published: (2024)
by: Tohme, Tony, et al.
Published: (2024)
FGDCC: Fine-Grained Deep Cluster Categorization -- A Framework for Intra-Class Variability Problems in Plant Classification
by: Filho, Luciano Araujo Dourado, et al.
Published: (2025)
by: Filho, Luciano Araujo Dourado, et al.
Published: (2025)
A Robust Governance for the AI Act: AI Office, AI Board, Scientific Panel, and National Authorities
by: Novelli, Claudio, et al.
Published: (2024)
by: Novelli, Claudio, et al.
Published: (2024)
From Passive Reuse to Active Reasoning: Grounding Large Language Models for Neuro-Symbolic Experience Replay
by: Xiao, Yanan, et al.
Published: (2026)
by: Xiao, Yanan, et al.
Published: (2026)
Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems
by: Chattopadhyay, Aniruddha, et al.
Published: (2025)
by: Chattopadhyay, Aniruddha, et al.
Published: (2025)
Generative AI in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity
by: Novelli, Claudio, et al.
Published: (2024)
by: Novelli, Claudio, et al.
Published: (2024)
Embodied AI: Emerging Risks and Opportunities for Policy Action
by: Perlo, Jared, et al.
Published: (2025)
by: Perlo, Jared, et al.
Published: (2025)
Worst-Case Symbolic Constraints Analysis and Generalisation with Large Language Models
by: Koh, Daniel, et al.
Published: (2025)
by: Koh, Daniel, et al.
Published: (2025)
Challenges and Best Practices in Corporate AI Governance:Lessons from the Biopharmaceutical Industry
by: Mökander, Jakob, et al.
Published: (2024)
by: Mökander, Jakob, et al.
Published: (2024)
MESSY Estimation: Maximum-Entropy based Stochastic and Symbolic densitY Estimation
by: Tohme, Tony, et al.
Published: (2023)
by: Tohme, Tony, et al.
Published: (2023)
HALO: An Ontology for Representing and Categorizing Hallucinations in Large Language Models
by: Nananukul, Navapat, et al.
Published: (2023)
by: Nananukul, Navapat, et al.
Published: (2023)
The Geometry of Categorical and Hierarchical Concepts in Large Language Models
by: Park, Kiho, et al.
Published: (2024)
by: Park, Kiho, et al.
Published: (2024)
Agentic AI Optimisation (AAIO): what it is, how it works, why it matters, and how to deal with it
by: Floridi, Luciano, et al.
Published: (2025)
by: Floridi, Luciano, et al.
Published: (2025)
How Large Language Models Need Symbolism
by: Deng, Xiaotie, et al.
Published: (2025)
by: Deng, Xiaotie, et al.
Published: (2025)
Systematic Characterization of the Effectiveness of Alignment in Large Language Models for Categorical Decisions
by: Kohane, Isaac
Published: (2024)
by: Kohane, Isaac
Published: (2024)
Symbol-LLM: Towards Foundational Symbol-centric Interface For Large Language Models
by: Xu, Fangzhi, et al.
Published: (2023)
by: Xu, Fangzhi, et al.
Published: (2023)
Using Large Language Models to Categorize Strategic Situations and Decipher Motivations Behind Human Behaviors
by: Xie, Yutong, et al.
Published: (2025)
by: Xie, Yutong, et al.
Published: (2025)
Analysis of Optimality of Large Language Models on Planning Problems
by: Bohnet, Bernd, et al.
Published: (2026)
by: Bohnet, Bernd, et al.
Published: (2026)
Grounding Methods for Neural-Symbolic AI
by: Ontiveros, Rodrigo Castellano, et al.
Published: (2025)
by: Ontiveros, Rodrigo Castellano, et al.
Published: (2025)
When Do Symbolic Solvers Enhance Reasoning in Large Language Models?
by: He, Zhiyuan, et al.
Published: (2025)
by: He, Zhiyuan, et al.
Published: (2025)
Why Do Large Language Models Generate Harmful Content?
by: Ganguli, Rajesh, et al.
Published: (2026)
by: Ganguli, Rajesh, et al.
Published: (2026)
Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses
by: Zheng, Xiaosen, et al.
Published: (2024)
by: Zheng, Xiaosen, et al.
Published: (2024)
Leveraging Large Language Models For Optimized Item Categorization using UNSPSC Taxonomy
by: Singh, Anmolika, et al.
Published: (2024)
by: Singh, Anmolika, et al.
Published: (2024)
Enhancing Large Language Model Efficiencyvia Symbolic Compression: A Formal Approach Towards Interpretability
by: AI, Lumen, et al.
Published: (2025)
by: AI, Lumen, et al.
Published: (2025)
Generating Symbolic World Models via Test-time Scaling of Large Language Models
by: Yu, Zhouliang, et al.
Published: (2025)
by: Yu, Zhouliang, et al.
Published: (2025)
Advancing Symbolic Integration in Large Language Models: Beyond Conventional Neurosymbolic AI
by: Rani, Maneeha, et al.
Published: (2025)
by: Rani, Maneeha, et al.
Published: (2025)
A Survey of Robotic Language Grounding: Tradeoffs between Symbols and Embeddings
by: Cohen, Vanya, et al.
Published: (2024)
by: Cohen, Vanya, et al.
Published: (2024)
Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models
by: Yang, Xiao-Wen, et al.
Published: (2025)
by: Yang, Xiao-Wen, et al.
Published: (2025)
Concept Arithmetics for Circumventing Concept Inhibition in Diffusion Models
by: Petsiuk, Vitali, et al.
Published: (2024)
by: Petsiuk, Vitali, et al.
Published: (2024)
SpotAgent: Grounding Visual Geo-localization in Large Vision-Language Models through Agentic Reasoning
by: Jia, Furong, et al.
Published: (2026)
by: Jia, Furong, et al.
Published: (2026)
In Context Learning and Reasoning for Symbolic Regression with Large Language Models
by: Sharlin, Samiha, et al.
Published: (2024)
by: Sharlin, Samiha, et al.
Published: (2024)
Symbol Grounding in Neuro-Symbolic AI: A Gentle Introduction to Reasoning Shortcuts
by: Marconato, Emanuele, et al.
Published: (2025)
by: Marconato, Emanuele, et al.
Published: (2025)
Similar Items
-
A Conjecture on a Fundamental Trade-Off between Certainty and Scope in Symbolic and Generative AI
by: Floridi, Luciano
Published: (2025) -
What Kind of Reasoning (if any) is an LLM actually doing? On the Stochastic Nature and Abductive Appearance of Large Language Models
by: Floridi, Luciano, et al.
Published: (2025) -
Evaluating Large Language Models on the Frame and Symbol Grounding Problems: A Zero-shot Benchmark
by: Oka, Shoko
Published: (2025) -
The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems
by: Mokander, Jakob, et al.
Published: (2024) -
Circumventing Safety Alignment in Large Language Models Through Embedding Space Toxicity Attenuation
by: Zhang, Zhibo, et al.
Published: (2025)