:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Takeshita, Sotaro, Takeshita, Yurina, Ruffinelli, Daniel, Ponzetto, Simone Paolo
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2508.17744
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

To MRL or not to MRL: Text Embeddings are Robust to Truncation Without Matryoshka Learning, Except In Heavy Truncation Scenarios
by: Takeshita, Sotaro, et al.
Published: (2026)

ROUGE-K: Do Your Summaries Have Keywords?
by: Takeshita, Sotaro, et al.
Published: (2024)

ACLSum: A New Dataset for Aspect-based Summarization of Scientific Publications
by: Takeshita, Sotaro, et al.
Published: (2024)

Enriching Social Science Research via Survey Item Linking
by: Tsereteli, Tornike, et al.
Published: (2024)

Approximation of Permutation Invariant Polynomials by Transformers: Efficient Construction in Column-Size
by: Takeshita, Naoki, et al.
Published: (2025)

Steering Language Models in Multi-Token Generation: A Case Study on Tense and Aspect
by: Klerings, Alina, et al.
Published: (2025)

Adversarial Example Generation using Evolutionary Multi-objective Optimization
by: Suzuki, Takahiro, et al.
Published: (2019)

Scaling Laws for Embedding Dimension in Information Retrieval
by: Killingback, Julian, et al.
Published: (2026)

Refining Joint Text and Source Code Embeddings for Retrieval Task with Parameter-Efficient Fine-Tuning
by: Galliamov, Karim, et al.
Published: (2024)

On the Impact of Performative Risk Minimization for Binary Random Variables
by: Tsoy, Nikita, et al.
Published: (2025)

Automated Random Embedding for Practical Bayesian Optimization with Unknown Effective Dimension
by: Qian, Hong, et al.
Published: (2026)

GATech at AbjadGenEval Shared Task: Multilingual Embeddings for Arabic Machine-Generated Text Classification
by: Khamis, Ahmed Khaled
Published: (2026)

GerAV: Towards New Heights in German Authorship Verification using Fine-Tuned LLMs on a New Benchmark
by: Kiefer, Lotta, et al.
Published: (2026)

Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQL
by: Papicchio, Simone, et al.
Published: (2025)

Time Series Embedding Methods for Classification Tasks: A Review
by: Irani, Habib, et al.
Published: (2025)

Residual Speech Embeddings for Tone Classification: Removing Linguistic Content to Enhance Paralinguistic Analysis
by: Ahbabi, Hamdan Al, et al.
Published: (2025)

The Rotary Position Embedding May Cause Dimension Inefficiency in Attention Heads for Long-Distance Retrieval
by: Chiang, Ting-Rui, et al.
Published: (2025)

Leveraging Non-linear Dimension Reduction and Random Walk Co-occurrence for Node Embedding
by: DeWolfe, Ryan
Published: (2026)

Higher Embedding Dimension Creates a Stronger World Model for a Simple Sorting Task
by: Bhalla, Brady, et al.
Published: (2025)

Hub-aware Random Walk Graph Embedding Methods for Classification
by: Tomčić, Aleksandar, et al.
Published: (2022)

Area under the ROC Curve has the Most Consistent Evaluation for Binary Classification
by: Li, Jing
Published: (2024)

TELEClass: Taxonomy Enrichment and LLM-Enhanced Hierarchical Text Classification with Minimal Supervision
by: Zhang, Yunyi, et al.
Published: (2024)

The Impact of Bootstrap Sampling Rate on Random Forest Performance in Regression Tasks
by: Iwaniuk, Michał, et al.
Published: (2025)

Finding Foundation Models for Time Series Classification with a PreText Task
by: Ismail-Fawaz, Ali, et al.
Published: (2023)

Measuring Intrinsic Dimension of Token Embeddings
by: Kataiwa, Takuya, et al.
Published: (2025)

On Probabilistic Embeddings in Optimal Dimension Reduction
by: Murray, Ryan, et al.
Published: (2024)

The Impact of Feature Scaling In Machine Learning: Effects on Regression and Classification Tasks
by: Pinheiro, João Manoel Herrera, et al.
Published: (2025)

Semantic Outlier Removal with Embedding Models and LLMs
by: Akbiyik, Eren, et al.
Published: (2025)

Optimal Embedding Dimension for Sparse Subspace Embeddings
by: Chenakkod, Shabarish, et al.
Published: (2023)

Understanding Generalization from Embedding Dimension and Distributional Convergence
by: Yu, Junjie, et al.
Published: (2026)

Improving Multimodal Classification of Social Media Posts by Leveraging Image-Text Auxiliary Tasks
by: Villegas, Danae Sánchez, et al.
Published: (2023)

Beyond the Hype: Embeddings vs. Prompting for Multiclass Classification Tasks
by: Kokkodis, Marios, et al.
Published: (2025)

Embedding Is (Almost) All You Need: Retrieval-Augmented Inference for Generalizable Genomic Prediction Tasks
by: Datta, Nirjhor, et al.
Published: (2025)

Assessing the Impact of Sequence Length Learning on Classification Tasks for Transformer Encoder Models
by: Baillargeon, Jean-Thomas, et al.
Published: (2022)

Minimizing Human Intervention in Online Classification
by: Réveillard, William, et al.
Published: (2025)

Towards Robust Knowledge Removal in Federated Learning with High Data Heterogeneity
by: Santi, Riccardo, et al.
Published: (2025)

Preserving Task-Relevant Information Under Linear Concept Removal
by: Holstege, Floris, et al.
Published: (2025)

The Impact of Background Removal on Performance of Neural Networks for Fashion Image Classification and Segmentation
by: Liang, Junhui, et al.
Published: (2023)

DimGrow: Memory-Efficient Field-level Embedding Dimension Search
by: Huang, Yihong, et al.
Published: (2025)

Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension
by: Filmus, Yuval, et al.
Published: (2023)