Image de couverture de livre

Fine-Tuning Small Embeddings for Elevated Performance

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Silwal, Biraj
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Interpretable Syntactic Representations Enable Hierarchical Word Vectors
par: Silwal, Biraj
Publié: (2024)

Prompt Tuning for Natural Language to SQL with Embedding Fine-Tuning and RAG
par: Jang, Jisoo, et autres
Publié: (2025)

Detecting Voice Phishing with Precision: Fine-Tuning Small Language Models
par: Sim, Ju Yong, et autres
Publié: (2025)

Fine-Tuning on Noisy Instructions: Effects on Generalization and Performance
par: Alajrami, Ahmed, et autres
Publié: (2025)

Unveiling Key Aspects of Fine-Tuning in Sentence Embeddings: A Representation Rank Analysis
par: Jung, Euna, et autres
Publié: (2024)

Internalizing Tool Knowledge in Small Language Models via QLoRA Fine-Tuning
par: Shemla, Yuval, et autres
Publié: (2026)

Dynamic Embedding of Hierarchical Visual Features for Efficient Vision-Language Fine-Tuning
par: Wei, Xinyu, et autres
Publié: (2025)

Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models
par: Barnett, Scott, et autres
Publié: (2024)

Not All Parameters Are Created Equal: Smart Isolation Boosts Fine-Tuning Performance
par: Wang, Yao, et autres
Publié: (2025)

Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning
par: Zhang, Mingtian, et autres
Publié: (2024)

Beyond QA Pairs: Assessing Parameter-Efficient Fine-Tuning for Fact Embedding in LLMs
par: Ratnakar, Shivam, et autres
Publié: (2025)

NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval
par: Zeighami, Sepanta, et autres
Publié: (2024)

Fine-Tuning Causal LLMs for Text Classification: Embedding-Based vs. Instruction-Based Approaches
par: Yousefiramandi, Amirhossein, et autres
Publié: (2025)

CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning
par: Yi, Biao, et autres
Publié: (2025)

Understanding the Performance and Estimating the Cost of LLM Fine-Tuning
par: Xia, Yuchen, et autres
Publié: (2024)

Embedding Enhancement via Fine-Tuned Language Models for Learner-Item Cognitive Modeling
par: Liu, Yuanhao, et autres
Publié: (2026)

Augmented Relevance Datasets with Fine-Tuned Small LLMs
par: Fitte-Rey, Quentin, et autres
Publié: (2025)

Generative Model for Small Molecules with Latent Space RL Fine-Tuning to Protein Targets
par: Sob, Ulrich A. Mbou, et autres
Publié: (2024)

Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning
par: Bi, Jing, et autres
Publié: (2024)

Prompting and Fine-Tuning of Small LLMs for Length-Controllable Telephone Call Summarization
par: Thulke, David, et autres
Publié: (2024)

REFINE on Scarce Data: Retrieval Enhancement through Fine-Tuning via Model Fusion of Embedding Models
par: Gupta, Ambuje, et autres
Publié: (2024)

Learning to Prioritize IT Tickets: A Comparative Evaluation of Embedding-based Approaches and Fine-Tuned Transformer Models
par: LÊ, Minh Tri, et autres
Publié: (2025)

LEMUR: A Corpus for Robust Fine-Tuning of Multilingual Law Embedding Models for Retrieval
par: Ahmadi, Narges Baba, et autres
Publié: (2026)

Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning
par: Patnaik, Sohan, et autres
Publié: (2025)

Accurate Prediction of Ligand-Protein Interaction Affinities with Fine-Tuned Small Language Models
par: Fauber, Ben
Publié: (2024)

Propulsion: Steering LLM with Tiny Fine-Tuning
par: Kowsher, Md, et autres
Publié: (2024)

Self-Evolution Fine-Tuning for Policy Optimization
par: Chen, Ruijun, et autres
Publié: (2024)

On the Impact of Fine-Tuning on Chain-of-Thought Reasoning
par: Lobo, Elita, et autres
Publié: (2024)

Rethinking Data Selection for Supervised Fine-Tuning
par: Shen, Ming
Publié: (2024)

ReFT: Reasoning with Reinforced Fine-Tuning
par: Luong, Trung Quoc, et autres
Publié: (2024)

Toward Secure Tuning: Mitigating Security Risks from Instruction Fine-Tuning
par: Du, Yanrui, et autres
Publié: (2024)

Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging
par: Farn, Hua, et autres
Publié: (2024)

Gradient Surgery for Safe LLM Fine-Tuning
par: Yi, Biao, et autres
Publié: (2025)

GIFT: Guided Fine-Tuning and Transfer for Enhancing Instruction-Tuned Language Models
par: Ruan, Zhiwen, et autres
Publié: (2026)

Small LLMs for Medical NLP: a Systematic Analysis of Few-Shot, Constraint Decoding, Fine-Tuning and Continual Pre-Training in Italian
par: Ferrazzi, Pietro, et autres
Publié: (2026)

Small Wins Big: Comparing Large Language Models and Domain Fine-Tuned Models for Sarcasm Detection in Code-Mixed Hinglish Text
par: Majumder, Bitan, et autres
Publié: (2026)

Honest AI: Fine-Tuning "Small" Language Models to Say "I Don't Know", and Reducing Hallucination in RAG
par: Chen, Xinxi, et autres
Publié: (2024)

Natural Language Fine-Tuning
par: Liu, Jia, et autres
Publié: (2024)

Anchored Supervised Fine-Tuning
par: Zhu, He, et autres
Publié: (2025)

NCL-UoR at SemEval-2026 Task 5: Embedding-Based Methods, Fine-Tuning, and LLMs for Word Sense Plausibility Rating
par: Wu, Tong, et autres
Publié: (2026)