Papers Sentiment Analysis
“Sentiment Analysis” 태그가 달린 논문 6,042편 · 필터 해제
An Empirical Study of Counterfactual Self-Explanations in LLMs
Large language models can easily generate explanations for their own outputs, but such self-explanations are not necessarily faithful to the model's behavior. We study this issue through counterfactual self-explanations,…
Natural Language InferenceSentiment AnalysisCan LLMs Follow the Pulse of a Crisis? Evaluating Crisis Sentiment in Bangladesh's July Uprising
Crisis sentiment analysis is especially challenging for low-resource languages such as Bangla, where language, context, and public reaction shift rapidly. We introduce UNRESTSENT200K, a Bangla crisis sentiment dataset wi…
Sentiment AnalysisGenerative Models Enhanced by Sequence Labelling and Aspect-Code Switching Improve Cross-lingual Aspect-Based Sentiment Analysis
Cross-lingual aspect-based sentiment analysis (ABSA) transfers knowledge from a source language with annotated data to a target language, enabling fine-grained sentiment analysis without annotated target-language data. W…
Sentiment AnalysisA Comprehensive Analysis of Arabic Natural Language Processing Research: Trends, Topic Evolution, and Research Gaps -- A Bibliometric and Topic-Based Study
Natural Language Processing (NLP) has grown rapidly over the past decade, driven by digital transformation in the Arab world, social media, and large language models (LLMs). Despite this growth, a comprehensive quantitat…
Sentiment AnalysisHelaBERT: Enhancing Sinhala Language Understanding with Dual Pooling Classification Head
We present HelaBERT, a family of two BERT-based masked language models pre-trained from scratch on approximately 1 billion tokens of Sinhala text sourced from MADLAD-400, CulturaX, and a custom corpus comprising news art…
Text ClassificationSentiment AnalysisSTAR-OPD: Structured Aspect-Cascade-Aware On-Policy Reward Distillation for ABSA Quadruple Extraction
Aspect-based sentiment analysis (ABSA) quadruple extraction requires jointly predicting target, aspect, opinion, and sentiment over reviews that often contain multiple fine-grained sentiment tuples. While large chain-of-…
Sentiment AnalysisSpeechSense: A Paralinguistic-Focused Dataset for Fine-Grained Speech Sentiment Analysis
Recent advances in AI have revolutionized speech processing, yet effective speech understanding requires discerning not just what is said, but how it is said. Speech Sentiment Analysis plays a critical role in decoding t…
Sentiment AnalysisSpeech RecognitionSpeech SynthesisAI-Driven Multiscenario Interest Rate Forecasting: A Proof of Concept for Banking Asset Management
This study focuses on developing an AI-supported prototype for multiperspective interest rate forecasting that combines classical econometric models with modern artificial intel-ligence methods. Tested in a major Europea…
Sentiment AnalysisLarge Language Models for Low-Resource Languages: A Conceptual Framework for an Electronic Explanatory Dictionary of the Tajik Language
This paper presents a conceptual framework for developing an electronic explanatory dictionary of the Tajik language using large language models (LLMs). The relevance of the work stems from the absence of a comprehensive…
parameter-efficient fine-tuningMachine TranslationSentiment AnalysisFinSMART: Financial Sentiment Analysis for Algorithmic Trading through Market-Aligned Reinforcement Learning
Recent advances in Generative AI have substantially improved financial sentiment analysis through post-trained financial large language models (LLMs). However, existing approaches remain confined to a market-agnostic, su…
Reinforcement LearningSentiment AnalysisFrom Minds to Models: The Intersection of Psychology and LLM Behaviours
Large language models (LLMs) are often compared with the human mind because their decision-making is complex, non-linear and difficult to interpret. Psychological methods developed to investigate unobservable mental proc…
Sentiment AnalysisBeyond Sentiment: Structured Information Extraction from Financial News
Financial sentiment analysis has become a standard component in news-driven stock prediction, yet it reduces rich, multi-dimensional news articles to a single polarity score. We hypothesize that financial news encodes mu…
Information ExtractionSentiment AnalysisFeature ImportanceAn empirical investigation into the properties of standard word embeddings
The embedding of word sequences into continuous vector spaces has been one of the most important developments in Natural Language Processing in the recent past. Such embeddings have found application in areas such as Aut…
Machine TranslationSpeech RecognitionSentiment AnalysisLanguage-Specific versus Cross-Lingual Knowledge Graphs for Implicit Aspect Identification in Arabic: A Comparative Study of Reasoning and Adaptation Strategies
Aspect-based sentiment analysis (ABSA) in Arabic must recover both explicitly stated aspects and implicit aspects that are never named in the text. Implicit identification typically relies on an auxiliary knowledge sourc…
Sentiment AnalysisKnowledge GraphsTriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis
Production LLM-based financial sentiment analysis faces a structural cost trap: most queries are trivially classifiable, yet expensive cloud reasoners process them all, and the bill scales linearly with user count. We pr…
Sentiment AnalysisTopoTuner: Topological Finetuning of Large Language Models
Full fine-tuning remains a strong way to adapt pretrained LLMs, but it updates all weights and can be expensive. LoRA reduces the number of trainable parameters, but it does not directly answer which pretrained component…
Sentiment AnalysisQuestion AnsweringExpanding the Lexicon of Ge'ez Based African Languages: A Comparative Study of Amharic and Tigrinya
Multilingual pre-trained language models such as XLM-R perform well for major languages but struggle with low-resource Ge'ez-script languages, largely due to high out-of-vocabulary (OOV) rates and excessive subword fragm…
Sentiment AnalysisQuestion AnsweringSegregate, Refine, Integrate: Decomposing Multimodal Fusion for Sentiment Analysis
Multimodal fusion must simultaneously refine modality-specific signals and model cross-modal interactions; two competing objectives typically entangled within the same operation. We propose \textbf{SeRIn} (\textbf{Se}gre…
Sentiment AnalysisA Longitudinal Analysis of Public Discourse on AI Ethics in Education Using Twitter Data
The rapid integration of artificial intelligence (AI) and generative AI (GenAI) into education presents significant opportunities to enhance teaching and learning, while raising ethical concerns about the responsible use…
Sentiment AnalysisLearning to Fine-tune Foundation Models under Resource Limitations
We study the problem of optimal continual fine-tuning for a pre-trained Foundation Model deployed at a resource-limited device. At each time slot, a new batch of training data arrives, and the controller is faced with tw…
Reinforcement LearningText ClassificationSentiment Analysis