LLaMA-Based Models for Aspect-Based Sentiment Analysis

Jakub Šmíd, Pavel Přibáň, Pavel Král
8/12/2025
cs.CL

No confident code implementation found for this paper. 3 possible matches can be shown below.

Abstract

While large language models (LLMs) show promise for various tasks, their performance in compound aspect-based sentiment analysis (ABSA) tasks lags behind fine-tuned models. However, the potential of LLMs fine-tuned for ABSA remains unexplored. This paper examines the capabilities of open-source LLMs fine-tuned for ABSA, focusing on LLaMA-based models. We evaluate the performance across four tasks and eight English datasets, finding that the fine-tuned Orca~2 model surpasses state-of-the-art results in all tasks. However, all models struggle in zero-shot and few-shot scenarios compared to fully fine-tuned ones. Additionally, we conduct error analysis to identify challenges faced by fine-tuned models.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Large-Scale Aspect-Based Sentiment Analysis with Reasoning-Infused LLMs

89% match2026

LACA: Improving Cross-lingual Aspect-Based Sentiment Analysis with LLM Data Augmentation

88% match2025

Exploring Large Language Models for Multimodal Sentiment Analysis: Challenges, Benchmarks, and Future Directions

88% match2024

Multi-Domain ABSA Conversation Dataset Generation via LLMs for Real-World Evaluation and Model Comparison

88% match2025

Advancing Cross-lingual Aspect-Based Sentiment Analysis with LLMs and Constrained Decoding for Sequence-to-Sequence Models

88% match2025

From Annotation to Adaptation: Metrics, Synthetic Data, and Aspect Extraction for Aspect-Based Sentiment Analysis with Large Language Models

87% match2025

Cite this paper

@article{md2025llamabased,
  title  = {LLaMA-Based Models for Aspect-Based Sentiment Analysis},
  author = {Jakub Šmíd and Pavel Přibáň and Pavel Král},
  year   = {2025},
  eprint = {2508.08649},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.08649v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2508.08649.svg)](https://codeofpaper.com/paper/2508.08649)

Discussion