Imagen de Portada

Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Xiong, Kai, Ding, Xiao, Liu, Ting, Qin, Bing, Xu, Dongliang, Yang, Qing, Liu, Hongtao, Cao, Yixin
Formato:	Preprint
Publicado:	2024
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Diagnosing and Remedying Knowledge Deficiencies in LLMs via Label-free Curricular Meaningful Learning
por: Xiong, Kai, et al.
Publicado: (2024)

Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate
por: Xiong, Kai, et al.
Publicado: (2023)

Com$^2$: A Causal-Guided Benchmark for Exploring Complex Commonsense Reasoning in Large Language Models
por: Xiong, Kai, et al.
Publicado: (2025)

Extending Context Window of Large Language Models from a Distributional Perspective
por: Wu, Yingsheng, et al.
Publicado: (2024)

DeepTool: Scaling Interleaved Deliberation in Tool-Integrated Reasoning via Process-Supervised Reinforcement Learning
por: He, Yang, et al.
Publicado: (2026)

Beyond Fixed Length: Bucket Pre-training is All You Need
por: Yang, Qing, et al.
Publicado: (2024)

Advancing Large Language Model Attribution through Self-Improving
por: Huang, Lei, et al.
Publicado: (2024)

Self-Route: Automatic Mode Switching via Capability Estimation for Efficient Reasoning
por: He, Yang, et al.
Publicado: (2025)

Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning
por: Zhao, Yang, et al.
Publicado: (2024)

Length Extrapolation of Transformers: A Survey from the Perspective of Positional Encoding
por: Zhao, Liang, et al.
Publicado: (2023)

Good Learners Think Their Thinking: Generative PRM Makes Large Reasoning Model More Efficient Math Learner
por: He, Tao, et al.
Publicado: (2025)

RU22Fact: Optimizing Evidence for Multilingual Explainable Fact-Checking on Russia-Ukraine Conflict
por: Zeng, Yirong, et al.
Publicado: (2024)

Towards Generalizable and Faithful Logic Reasoning over Natural Language via Resolution Refutation
por: Sun, Zhouhao, et al.
Publicado: (2024)

Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling
por: Yang, Linyao, et al.
Publicado: (2023)

Supervised Fine-Tuning Achieve Rapid Task Adaption Via Alternating Attention Head Activation Patterns
por: Zhao, Yang, et al.
Publicado: (2024)

CrossICL: Cross-Task In-Context Learning via Unsupervised Demonstration Transfer
por: Gao, Jinglong, et al.
Publicado: (2025)

GlobeSumm: A Challenging Benchmark Towards Unifying Multi-lingual, Cross-lingual and Multi-document News Summarization
por: Ye, Yangfan, et al.
Publicado: (2024)

A Theory for Length Generalization in Learning to Reason
por: Xiao, Changnan, et al.
Publicado: (2024)

Causal-Guided Active Learning for Debiasing Large Language Models
por: Du, Li, et al.
Publicado: (2024)

Enhancing Complex Causality Extraction via Improved Subtask Interaction and Knowledge Fusion
por: Gao, Jinglong, et al.
Publicado: (2024)

CAPO: Towards Enhancing LLM Reasoning through Generative Credit Assignment
por: Xie, Guofu, et al.
Publicado: (2025)

ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networks
por: Xiong, Kai, et al.
Publicado: (2022)

Beyond Similarity: A Gradient-based Graph Method for Instruction Tuning Data Selection
por: Zhao, Yang, et al.
Publicado: (2025)

SAPT: A Shared Attention Framework for Parameter-Efficient Continual Learning of Large Language Models
por: Zhao, Weixiang, et al.
Publicado: (2024)

Review-LLM: Harnessing Large Language Models for Personalized Review Generation
por: Peng, Qiyao, et al.
Publicado: (2024)

Information Gain-Guided Causal Intervention for Autonomous Debiasing Large Language Models
por: Sun, Zhouhao, et al.
Publicado: (2025)

CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models
por: Qian, Cheng, et al.
Publicado: (2023)

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models
por: Yeh, Cheng-Kai, et al.
Publicado: (2025)

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models
por: Zhang, Ruiqi, et al.
Publicado: (2025)

GR-Ben: A General Reasoning Benchmark for Evaluating Process Reward Models
por: Sun, Zhouhao, et al.
Publicado: (2026)

How does Architecture Influence the Base Capabilities of Pre-trained Language Models? A Case Study Based on FFN-Wider and MoE Transformers
por: Lu, Xin, et al.
Publicado: (2024)

Scaling Laws for Fact Memorization of Large Language Models
por: Lu, Xingyu, et al.
Publicado: (2024)

Large Language Models Are Still Misled by Simple Bias Ensembles
por: Sun, Zhouhao, et al.
Publicado: (2025)

GraCoRe: Benchmarking Graph Comprehension and Complex Reasoning in Large Language Models
por: Yuan, Zike, et al.
Publicado: (2024)

HyperGuide: Hyperbolic Guidance for Efficient Multi-Step Reasoning in Large Language Models
por: Liu, Yuyu, et al.
Publicado: (2026)

Thinking with Visual Abstract: Enhancing Multimodal Reasoning via Visual Abstraction
por: Liu, Dairu, et al.
Publicado: (2025)

Learning Visual Abstract Reasoning through Dual-Stream Networks
por: Zhao, Kai, et al.
Publicado: (2024)

SCALER:Synthetic Scalable Adaptive Learning Environment for Reasoning
por: Xu, Caijun, et al.
Publicado: (2026)

Structured Chemistry Reasoning with Large Language Models
por: Ouyang, Siru, et al.
Publicado: (2023)

Aligning Translation-Specific Understanding to General Understanding in Large Language Models
por: Huang, Yichong, et al.
Publicado: (2024)