Cover Image

Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Qingyao, Fu, Lingyue, Zhang, Weiming, Chen, Xianyu, Yu, Jingwei, Xia, Wei, Zhang, Weinan, Tang, Ruiming, Yu, Yong
Format:	Preprint
Published:	2023
Subjects:	Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LLM4CD: Leveraging Large Language Models for Open-World Knowledge Augmented Cognitive Diagnosis
by: Zhang, Weiming, et al.
Published: (2025)

NL-Debugging: Exploiting Natural Language as an Intermediate Representation for Code Debugging
by: Zhang, Weiming, et al.
Published: (2025)

Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation
by: Li, Qingyao, et al.
Published: (2024)

RethinkMCTS: Refining Erroneous Thoughts in Monte Carlo Tree Search for Code Generation
by: Li, Qingyao, et al.
Published: (2024)

Large Language Models Make Sample-Efficient Recommender Systems
by: Lin, Jianghao, et al.
Published: (2024)

Generative Representational Learning of Foundation Models for Recommendation
by: Zhou, Zheli, et al.
Published: (2025)

Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations
by: Xi, Yunjia, et al.
Published: (2026)

SINKT: A Structure-Aware Inductive Knowledge Tracing Model with Large Language Model
by: Fu, Lingyue, et al.
Published: (2024)

A Survey on Multi-Turn Interaction Capabilities of Large Language Models
by: Zhang, Chen, et al.
Published: (2025)

MassTool: A Multi-Task Search-Based Tool Retrieval Framework for Large Language Models
by: Lin, Jianghao, et al.
Published: (2025)

LogitsCoder: Towards Efficient Chain-of-Thought Path Search via Logits Preference Decoding for Code Generation
by: Chen, Jizheng, et al.
Published: (2026)

CodeApex: A Bilingual Programming Evaluation Benchmark for Large Language Models
by: Fu, Lingyue, et al.
Published: (2023)

CATArena: Evaluating Evolutionary Capabilities of Code Agents via Iterative Tournaments
by: Fu, Lingyue, et al.
Published: (2025)

CodeGRAG: Bridging the Gap between Natural Language and Programming Language via Graphical Retrieval Augmented Generation
by: Du, Kounianhua, et al.
Published: (2024)

Performance Law of Large Language Models
by: Wu, Chuhan, et al.
Published: (2024)

DebugTA: An LLM-Based Agent for Simplifying Debugging and Teaching in Programming Education
by: Fu, Lingyue, et al.
Published: (2025)

AdvKT: An Adversarial Multi-Step Training Framework for Knowledge Tracing
by: Fu, Lingyue, et al.
Published: (2025)

Improving Natural Language Capability of Code Large Language Model
by: Li, Wei, et al.
Published: (2024)

FEEL: A Framework for Evaluating Emotional Support Capability with Large Language Models
by: Zhang, Huaiwen, et al.
Published: (2024)

Towards Efficient and Effective Unlearning of Large Language Models for Recommendation
by: Wang, Hangyu, et al.
Published: (2024)

Automatically Benchmarking LLM Code Agents through Agent-Driven Annotation and Evaluation
by: Fu, Lingyue, et al.
Published: (2025)

ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction
by: Lin, Jianghao, et al.
Published: (2023)

Language-Specific Neurons: The Key to Multilingual Capabilities in Large Language Models
by: Tang, Tianyi, et al.
Published: (2024)

Large Language Models are Demonstration Pre-Selectors for Themselves
by: Jin, Jiarui, et al.
Published: (2025)

ZPD Detector: Data Selection via Capability-Difficulty Alignment for Large Language Models
by: Yang, Bo, et al.
Published: (2026)

MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
by: Xi, Yunjia, et al.
Published: (2024)

Adaptive Tool Use in Large Language Models with Meta-Cognition Trigger
by: Li, Wenjun, et al.
Published: (2025)

Towards Generalist Prompting for Large Language Models by Mental Models
by: Guan, Haoxiang, et al.
Published: (2024)

MIA-Tuner: Adapting Large Language Models as Pre-training Text Detector
by: Fu, Wenjie, et al.
Published: (2024)

Confidence in Large Language Model Evaluation: A Bayesian Approach to Limited-Sample Challenges
by: Xiao, Xiao, et al.
Published: (2025)

WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation Models
by: Wang, Rui, et al.
Published: (2025)

MoreauPruner: Robust Pruning of Large Language Models against Weight Perturbations
by: Wang, Zixiao, et al.
Published: (2024)

Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models
by: Xi, Yunjia, et al.
Published: (2024)

LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models
by: Li, Haitao, et al.
Published: (2024)

BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models
by: Sun, Haotian, et al.
Published: (2024)

Evaluating the Generation Capabilities of Large Chinese Language Models
by: Zeng, Hui, et al.
Published: (2023)

Evaluating Accounting Reasoning Capabilities of Large Language Models
by: Zhou, Jie, et al.
Published: (2026)

A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models
by: Zheng, Congmin, et al.
Published: (2025)

Adapting Large Language Models for Time Series Modeling via a Novel Parameter-efficient Adaptation Method
by: Zhang, Juyuan, et al.
Published: (2025)

Investigating Numerical Translation with Large Language Models
by: Tang, Wei, et al.
Published: (2025)