Buchumschlag

Teaching Small Language Models to Learn Logic through Meta-Learning

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Bertolazzi, Leonardo, Guzmán, Manuel Vargas, Bernardi, Raffaella, Malicki, Maciej, Szymanik, Jakub
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Computation and Language
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Hybrid Models for Natural Language Reasoning: The Case of Syllogistic Logic
von: Guzmán, Manuel Vargas, et al.
Veröffentlicht: (2025)

How Language Models Conflate Logical Validity with Plausibility: A Representational Analysis of Content Effects
von: Bertolazzi, Leonardo, et al.
Veröffentlicht: (2025)

A Systematic Analysis of Large Language Models as Soft Reasoners: The Case of Syllogistic Inferences
von: Bertolazzi, Leonardo, et al.
Veröffentlicht: (2024)

The Validation Gap: A Mechanistic Analysis of How Language Models Compute Arithmetic but Fail to Validate It
von: Bertolazzi, Leonardo, et al.
Veröffentlicht: (2025)

Black Big Boxes: Tracing Adjective Order Preferences in Large Language Models
von: Jumelet, Jaap, et al.
Veröffentlicht: (2024)

Learning to Ask Informative Questions: Enhancing LLMs with Preference Optimization and Expected Information Gain
von: Mazzaccara, Davide, et al.
Veröffentlicht: (2024)

Learning Dynamics of Meta-Learning in Small Model Pretraining
von: Africa, David Demitri, et al.
Veröffentlicht: (2025)

Explainable Behavior Cloning: Teaching Large Language Model Agents through Learning by Demonstration
von: Guan, Yanchu, et al.
Veröffentlicht: (2024)

Tolerance Principle and Small Language Model Learning
von: Friedman, Adam E., et al.
Veröffentlicht: (2026)

Teaching Language Models to Self-Improve by Learning from Language Feedback
von: Hu, Chi, et al.
Veröffentlicht: (2024)

Language Modeling with Learned Meta-Tokens
von: Shah, Alok N., et al.
Veröffentlicht: (2025)

Improving In-Context Learning with Small Language Model Ensembles
von: Mojarradi, M. Mehdi, et al.
Veröffentlicht: (2024)

Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perception
von: Zhao, Jihao, et al.
Veröffentlicht: (2024)

Triangulating LLM Progress through Benchmarks, Games, and Cognitive Tests
von: Momentè, Filippo, et al.
Veröffentlicht: (2025)

The Price of Thought: A Multilingual Analysis of Reasoning, Performance, and Cost of Negotiation in Large Language Models
von: Hakimov, Sherzod, et al.
Veröffentlicht: (2025)

LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?
von: Wang, Jingyuan, et al.
Veröffentlicht: (2025)

Teaching Language Models to Self-Improve through Interactive Demonstrations
von: Yu, Xiao, et al.
Veröffentlicht: (2023)

Small Language Models Improve Giants by Rewriting Their Outputs
von: Vernikos, Giorgos, et al.
Veröffentlicht: (2023)

Small Language Models Reshape Higher Education: Courses, Textbooks, and Teaching
von: Zhang, Jian, et al.
Veröffentlicht: (2025)

Reasoning Capabilities of Large Language Models. Lessons Learned from General Game Playing
von: Świechowski, Maciej, et al.
Veröffentlicht: (2026)

A logic of co-valuations
von: Malicki, Maciej
Veröffentlicht: (2025)

Isomorphism of almost locally compact Polish metric structures
von: Malicki, Maciej
Veröffentlicht: (2025)

Isomorphism of locally compact Polish metric structures
von: Malicki, Maciej
Veröffentlicht: (2022)

Learning to Learn from Language Feedback with Social Meta-Learning
von: Cook, Jonathan, et al.
Veröffentlicht: (2026)

Integrating Physician Diagnostic Logic into Large Language Models: Preference Learning from Process Feedback
von: Dou, Chengfeng, et al.
Veröffentlicht: (2024)

In-context Learning vs. Instruction Tuning: The Case of Small and Multilingual Language Models
von: Ponce, David, et al.
Veröffentlicht: (2025)

Learning to Seek Help: Dynamic Collaboration Between Small and Large Language Models
von: Zeng, Hang, et al.
Veröffentlicht: (2026)

Learning to Reason via Self-Iterative Process Feedback for Small Language Models
von: Chen, Kaiyuan, et al.
Veröffentlicht: (2024)

Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks
von: Kim, Hyunjae, et al.
Veröffentlicht: (2024)

Recursive Numeral Systems Optimize the Trade‐off Between Lexicon Size and Average Morphosyntactic Complexity
von: Milica Denić, et al.
Veröffentlicht: (2024)

Teaching Language Models to Critique via Reinforcement Learning
von: Xie, Zhihui, et al.
Veröffentlicht: (2025)

Learning Semantic Structure through First-Order-Logic Translation
von: Chaturvedi, Akshay, et al.
Veröffentlicht: (2024)

Meta-aware Learning in text-to-SQL Large Language Model
von: Zhang, Wenda
Veröffentlicht: (2025)

Massive Editing for Large Language Models via Meta Learning
von: Tan, Chenmien, et al.
Veröffentlicht: (2023)

LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks
von: Bavaresco, Anna, et al.
Veröffentlicht: (2024)

AS-ES Learning: Towards Efficient CoT Learning in Small Models
von: Xi, Nuwa, et al.
Veröffentlicht: (2024)

Reason from Fallacy: Enhancing Large Language Models' Logical Reasoning through Logical Fallacy Understanding
von: Li, Yanda, et al.
Veröffentlicht: (2024)

Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning
von: Patnaik, Sohan, et al.
Veröffentlicht: (2025)

Advancing Tool-Augmented Large Language Models via Meta-Verification and Reflection Learning
von: Ma, Zhiyuan, et al.
Veröffentlicht: (2025)

Efficient Continual Learning for Small Language Models with a Discrete Key-Value Bottleneck
von: Diera, Andor, et al.
Veröffentlicht: (2024)