arXiv Machine Learning June 9, 2026 By Muhammad Jawad Mufti, Omar Hammad, MD. Mahfuzur Rahman

Improving User Experience with Personalized Review Ranking and Summarization

Read the original on arXiv Machine Learning →

arXiv:2601. 05261v2 Announce Type: replace-cross Abstract: Online consumer reviews are important decision-support resources in e-commerce, yet the increasing volume of reviews often creates information overload and makes it difficult for users to identify content that matches their individual preferences.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI

Jul 14

Large Language Models for Token-Efficient and Semantic-Preserving Opinion Summarization

arXiv:2607. 10825v1 Announce Type: cross Abstract: Opinionated text - spanning product reviews, hotel feedback, and social posts - captures rich signals about user experiences, preferences, and concerns.

By Fabrizio Marozzo, Stefano Iannicelli

llms nlp

arXiv AI

Jun 24

Evaluating LLM Usage for Efficient and Explainable Numerical and Classified Implicit Sentiment Analysis of Product Desirability

arXiv:2606. 23701v1 Announce Type: cross Abstract: Qualitative product feedback can reveal nuanced user experiences, but its implicit sentiment is difficult to measure.

By Sherri Weitl-Harms, John Hastings

llms nlp safety

arXiv AI

Jun 2

SentimentLens: Reconciling Sentiment and Ratings via Dual-Modality in the Hospitality Sector

arXiv:2606. 00084v1 Announce Type: cross Abstract: Online travel platforms generate vast volumes of user-generated hotel reviews, offering rich opportunities to understand traveler experiences at scale.

By Dineth Jayakody, Pasindu Thenahandi, Sampath Jayarathna

nlp multimodal

arXiv AI

Jun 4

Rethinking Sales Lead Scoring with LLM-based Hierarchical Preference Ranking

arXiv:2606. 04387v1 Announce Type: cross Abstract: Sales lead conversion in high-stakes domains (e.

By Chenyu Zhang, Yiwen Liu, Yin Sun, Xinyuan Zhang, Yuji Cao, Junming Jiao, Juyi Qiao

llms benchmarks safety

arXiv AI

Aug 6

MIDAS: Multi-LLM Iterative Data-Adaptive Summarization

arXiv:2608. 04307v1 Announce Type: cross Abstract: Text summarization is deceptively difficult.

By Karen Lee, Dhanashree Balaram, Seojun Shon, Umair Rasheed

llms nlp benchmarks

arXiv Machine Learning

Jul 7

SalAngaBhava: A Sinhala Market Dataset for Aspect-based Sentiment Analysis

arXiv:2607. 05259v1 Announce Type: cross Abstract: Sentiment analysis has been a primary domain under Natural Language Processing (NLP) from its inception as it plays a vital role in both real-world and research applications.

By Lakshani Galwatta, Nisansa de Silva, Sarangi Aththanayake, Adithya Galwatta

nlp benchmarks

Related stories

Large Language Models for Token-Efficient and Semantic-Preserving Opinion Summarization

Evaluating LLM Usage for Efficient and Explainable Numerical and Classified Implicit Sentiment Analysis of Product Desirability

SentimentLens: Reconciling Sentiment and Ratings via Dual-Modality in the Hospitality Sector

Rethinking Sales Lead Scoring with LLM-based Hierarchical Preference Ranking

MIDAS: Multi-LLM Iterative Data-Adaptive Summarization

SalAngaBhava: A Sinhala Market Dataset for Aspect-based Sentiment Analysis