Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective
Fuente:
arXiv
Saved in:
| Main Authors: | Ghosh, Bishwamittra, Das, Soumi, Speicher, Till, Wu, Qinyuan, Khan, Mohammad Aflah, Garg, Deepak, Gummadi, Krishna P., Terzi, Evimaria |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Rethinking Memorization Measures and their Implications in Large Language Models
by: Ghosh, Bishwamittra, et al.
Published: (2025)
by: Ghosh, Bishwamittra, et al.
Published: (2025)
Understanding Memorisation in LLMs: Dynamics, Influencing Factors, and Implications
by: Speicher, Till, et al.
Published: (2024)
by: Speicher, Till, et al.
Published: (2024)
Revisiting Privacy, Utility, and Efficiency Trade-offs when Fine-Tuning Large Language Models
by: Das, Soumi, et al.
Published: (2025)
by: Das, Soumi, et al.
Published: (2025)
Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction
by: Wu, Qinyuan, et al.
Published: (2024)
by: Wu, Qinyuan, et al.
Published: (2024)
Rote Learning Considered Useful: Generalizing over Memorized Data in LLMs
by: Wu, Qinyuan, et al.
Published: (2025)
by: Wu, Qinyuan, et al.
Published: (2025)
In Agents We Trust, but Who Do Agents Trust? Latent Source Preferences Steer LLM Generations
by: Khan, Mohammad Aflah, et al.
Published: (2026)
by: Khan, Mohammad Aflah, et al.
Published: (2026)
Understanding the Role of Invariance in Transfer Learning
by: Speicher, Till, et al.
Published: (2024)
by: Speicher, Till, et al.
Published: (2024)
Fractional Rotation, Full Potential? Investigating Performance and Convergence of Partial RoPE
by: Khan, Mohammad Aflah, et al.
Published: (2026)
by: Khan, Mohammad Aflah, et al.
Published: (2026)
Computing Approximate Pareto Frontiers for Submodular Utility and Cost Tradeoffs
by: Vombatkere, Karan, et al.
Published: (2026)
by: Vombatkere, Karan, et al.
Published: (2026)
Team Formation amidst Conflicts
by: Nikolaou, Iasonas, et al.
Published: (2024)
by: Nikolaou, Iasonas, et al.
Published: (2024)
Investigating the Effects of Fairness Interventions Using Pointwise Representational Similarity
by: Kolling, Camila, et al.
Published: (2023)
by: Kolling, Camila, et al.
Published: (2023)
Logical Consistency of Large Language Models in Fact-checking
by: Ghosh, Bishwamittra, et al.
Published: (2024)
by: Ghosh, Bishwamittra, et al.
Published: (2024)
LoRA on the Go: Instance-level Dynamic LoRA Selection and Merging
by: Lee, Seungeon, et al.
Published: (2025)
by: Lee, Seungeon, et al.
Published: (2025)
TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability
by: Khan, Mohammad Aflah, et al.
Published: (2025)
by: Khan, Mohammad Aflah, et al.
Published: (2025)
Advancing Natural Language Formalization to First Order Logic with Fine-tuned LLMs
by: Vossel, Felix, et al.
Published: (2025)
by: Vossel, Felix, et al.
Published: (2025)
Forming Coordinated Teams that Balance Task Coverage and Expert Workload
by: Vombatkere, Karan, et al.
Published: (2025)
by: Vombatkere, Karan, et al.
Published: (2025)
Testing the Limits of Truth Directions in LLMs
by: Poulis, Angelos, et al.
Published: (2026)
by: Poulis, Angelos, et al.
Published: (2026)
A QUBO Framework for Team Formation
by: Vombatkere, Karan, et al.
Published: (2025)
by: Vombatkere, Karan, et al.
Published: (2025)
Understanding team collapse via probabilistic graphical models
by: Nikolaou, Iasonas, et al.
Published: (2024)
by: Nikolaou, Iasonas, et al.
Published: (2024)
To Call or Not to Call: A Framework to Assess and Optimize LLM Tool Calling
by: Wu, Qinyuan, et al.
Published: (2026)
by: Wu, Qinyuan, et al.
Published: (2026)
Assertion Detection Large Language Model In-context Learning LoRA Fine-tuning
by: Ji, Yuelyu, et al.
Published: (2024)
by: Ji, Yuelyu, et al.
Published: (2024)
Online Two-Stage Submodular Maximization
by: Nikolaou, Iasonas, et al.
Published: (2025)
by: Nikolaou, Iasonas, et al.
Published: (2025)
FACEGroup: Feasible and Actionable Counterfactual Explanations for Group Fairness
by: Fragkathoulas, Christos, et al.
Published: (2024)
by: Fragkathoulas, Christos, et al.
Published: (2024)
Mechanistic Fine-tuning for In-context Learning
by: Cho, Hakaze, et al.
Published: (2025)
by: Cho, Hakaze, et al.
Published: (2025)
The Algorithmic Self-Portrait: Deconstructing Memory in ChatGPT
by: Dash, Abhisek, et al.
Published: (2026)
by: Dash, Abhisek, et al.
Published: (2026)
Sensitivity of Small Language Models to Fine-tuning Data Contamination
by: Scaria, Nicy, et al.
Published: (2025)
by: Scaria, Nicy, et al.
Published: (2025)
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models
by: Yin, Haoteng, et al.
Published: (2024)
by: Yin, Haoteng, et al.
Published: (2024)
Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models
by: Chen, Pin-Yu, et al.
Published: (2025)
by: Chen, Pin-Yu, et al.
Published: (2025)
Online Submodular Maximization via Online Convex Optimization
by: Salem, Tareq Si, et al.
Published: (2023)
by: Salem, Tareq Si, et al.
Published: (2023)
Probing Critical Learning Dynamics of PLMs for Hate Speech Detection
by: Masud, Sarah, et al.
Published: (2024)
by: Masud, Sarah, et al.
Published: (2024)
Active Fourier Auditor for Estimating Distributional Properties of ML Models
by: Ajarra, Ayoub, et al.
Published: (2024)
by: Ajarra, Ayoub, et al.
Published: (2024)
Hubble: a Model Suite to Advance the Study of LLM Memorization
by: Wei, Johnny Tian-Zheng, et al.
Published: (2025)
by: Wei, Johnny Tian-Zheng, et al.
Published: (2025)
Semi-supervised Fine-tuning for Large Language Models
by: Luo, Junyu, et al.
Published: (2024)
by: Luo, Junyu, et al.
Published: (2024)
Fine-tuning Large Language Models with Sequential Instructions
by: Hu, Hanxu, et al.
Published: (2024)
by: Hu, Hanxu, et al.
Published: (2024)
Sparse Matrix in Large Language Model Fine-tuning
by: He, Haoze, et al.
Published: (2024)
by: He, Haoze, et al.
Published: (2024)
Fine-tuning Large Language Models for Entity Matching
by: Steiner, Aaron, et al.
Published: (2024)
by: Steiner, Aaron, et al.
Published: (2024)
Fed-EC: Bandwidth-Efficient Clustering-Based Federated Learning For Autonomous Visual Robot Navigation
by: Gummadi, Shreya, et al.
Published: (2024)
by: Gummadi, Shreya, et al.
Published: (2024)
Fine-tuning vs Prompting, Can Language Models Understand Human Values?
by: Sun, Pingwei
Published: (2024)
by: Sun, Pingwei
Published: (2024)
From Practicum to Real Classroom: Does Experience Change Perceived Self-efficacy Beliefs of English Language Teachers?
by: Canan Terzi
Published: (2022)
by: Canan Terzi
Published: (2022)
Understanding Syllogistic Reasoning in LLMs from Formal and Natural Language Perspectives
by: Poddar, Aheli, et al.
Published: (2025)
by: Poddar, Aheli, et al.
Published: (2025)
Similar Items
-
Rethinking Memorization Measures and their Implications in Large Language Models
by: Ghosh, Bishwamittra, et al.
Published: (2025) -
Understanding Memorisation in LLMs: Dynamics, Influencing Factors, and Implications
by: Speicher, Till, et al.
Published: (2024) -
Revisiting Privacy, Utility, and Efficiency Trade-offs when Fine-Tuning Large Language Models
by: Das, Soumi, et al.
Published: (2025) -
Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction
by: Wu, Qinyuan, et al.
Published: (2024) -
Rote Learning Considered Useful: Generalizing over Memorized Data in LLMs
by: Wu, Qinyuan, et al.
Published: (2025)