Copertina

Learning Beyond the Surface: How Far Can Continual Pre-Training with LoRA Enhance LLMs' Domain-Specific Insight Learning?

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Pezeshkpour, Pouya, Hruschka, Estevam
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Insight-RAG: Enhancing LLMs with Insight-Driven Augmentation
di: Pezeshkpour, Pouya, et al.
Pubblicazione: (2025)

AutoPyVerifier: Learning Compact Executable Verifiers for Large Language Model Outputs
di: Pezeshkpour, Pouya, et al.
Pubblicazione: (2026)

From Task Solving to Robust Real-World Adaptation in LLM Agents
di: Pezeshkpour, Pouya, et al.
Pubblicazione: (2026)

Multi-Conditional Ranking with Large Language Models
di: Pezeshkpour, Pouya, et al.
Pubblicazione: (2024)

Align then Train: Efficient Retrieval Adapter Learning
di: Maekawa, Seiji, et al.
Pubblicazione: (2026)

Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions
di: Pezeshkpour, Pouya, et al.
Pubblicazione: (2024)

Evaluating Bias in LLMs for Job-Resume Matching: Gender, Race, and Education
di: Iso, Hayate, et al.
Pubblicazione: (2025)

From Proof to Program: Characterizing Tool-Induced Reasoning Hallucinations in Large Language Models
di: Bayat, Farima Fatahi, et al.
Pubblicazione: (2025)

Less is More for Long Document Summary Evaluation by LLMs
di: Wu, Yunshu, et al.
Pubblicazione: (2023)

From Single to Multi: How LLMs Hallucinate in Multi-Document Summarization
di: Belem, Catarina G., et al.
Pubblicazione: (2024)

Sci-LoRA: Mixture of Scientific LoRAs for Cross-Domain Lay Paraphrasing
di: Cheng, Ming, et al.
Pubblicazione: (2025)

Mitigating Unintended Memorization with LoRA in Federated Learning for LLMs
di: Bossy, Thierry, et al.
Pubblicazione: (2025)

Improving LoRA with Variational Learning
di: Cong, Bai, et al.
Pubblicazione: (2025)

Towards Reliable Benchmarking: A Contamination Free, Controllable Evaluation Framework for Multi-step LLM Function Calling
di: Maekawa, Seiji, et al.
Pubblicazione: (2025)

LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation
di: Zhou, Hongyun, et al.
Pubblicazione: (2024)

LoRA Learns Less and Forgets Less
di: Biderman, Dan, et al.
Pubblicazione: (2024)

AFA-LoRA: Enabling Non-Linear Adaptations in LoRA with Activation Function Annealing
di: Li, Jiacheng, et al.
Pubblicazione: (2025)

DLP-LoRA: Efficient Task-Specific LoRA Fusion with a Dynamic, Lightweight Plugin for Large Language Models
di: Zhang, Yuxuan, et al.
Pubblicazione: (2024)

LoRA on the Go: Instance-level Dynamic LoRA Selection and Merging
di: Lee, Seungeon, et al.
Pubblicazione: (2025)

Mixture of LoRA Experts
di: Wu, Xun, et al.
Pubblicazione: (2024)

Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
di: Qin, Haotong, et al.
Pubblicazione: (2024)

Enhancing Learned Knowledge in LoRA Adapters Through Efficient Contrastive Decoding on Ascend NPUs
di: Heisler, Morgan Lindsay, et al.
Pubblicazione: (2025)

LoRA Soups: Merging LoRAs for Practical Skill Composition Tasks
di: Prabhakar, Akshara, et al.
Pubblicazione: (2024)

LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
di: Yen, Jui-Nan, et al.
Pubblicazione: (2024)

Mixed Signals: Decoding VLMs' Reasoning and Underlying Bias in Vision-Language Conflict
di: Pezeshkpour, Pouya, et al.
Pubblicazione: (2025)

LoRA-PAR: A Flexible Dual-System LoRA Partitioning Approach to Efficient LLM Fine-Tuning
di: Huang, Yining, et al.
Pubblicazione: (2025)

A Note on LoRA
di: Fomenko, Vlad, et al.
Pubblicazione: (2024)

HyperAdaLoRA: Accelerating LoRA Rank Allocation During Training via Hypernetworks without Sacrificing Performance
di: Zhang, Hao, et al.
Pubblicazione: (2025)

LoRA-Mini : Adaptation Matrices Decomposition and Selective Training
di: Singh, Ayush, et al.
Pubblicazione: (2024)

LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs
di: Davoodi, Arash Gholami, et al.
Pubblicazione: (2024)

A Dynamic Self-Evolving Extraction System
di: Amin-Naseri, Moin, et al.
Pubblicazione: (2026)

KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation
di: Azimi, Rambod, et al.
Pubblicazione: (2024)

Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning
di: Xia, Wenhan, et al.
Pubblicazione: (2024)

Uncertainty quantification in fine-tuned LLMs using LoRA ensembles
di: Balabanov, Oleksandr, et al.
Pubblicazione: (2024)

MTL-LoRA: Low-Rank Adaptation for Multi-Task Learning
di: Yang, Yaming, et al.
Pubblicazione: (2024)

Adaptive Selection of LoRA Components in Privacy-Preserving Federated Learning
di: Kim, Myoungjun, et al.
Pubblicazione: (2026)

ELDER: Enhancing Lifelong Model Editing with Mixture-of-LoRA
di: Li, Jiaang, et al.
Pubblicazione: (2024)

Towards Specialized Generalists: A Multi-Task MoE-LoRA Framework for Domain-Specific LLM Adaptation
di: Yang, Yuxin, et al.
Pubblicazione: (2026)

Dynamic Adaptation of LoRA Fine-Tuning for Efficient and Task-Specific Optimization of Large Language Models
di: Liao, Xiaoxuan, et al.
Pubblicazione: (2025)

Challenges in Adapting Multilingual LLMs to Low-Resource Languages using LoRA PEFT Tuning
di: Khade, Omkar, et al.
Pubblicazione: (2024)