tf–idf
PulseAugur coverage of tf–idf — every cluster mentioning tf–idf across labs, papers, and developer communities, ranked by signal.
3 天有情绪数据
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Small TF-IDF classifier beats large fine-tuned model on tweet classification
A smaller, 1.9 MB classifier model, utilizing TF-IDF and Logistic Regression, outperformed a larger, 269 MB fine-tuned model in classifying customer support tweets. The smaller model achieved this by focusing on efficie…
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AI struggles with nuanced tasks like peer review and expert identification
Two new research papers explore the limitations of current AI models in specialized academic tasks. One study, Sem-Detect, proposes a method to distinguish AI-generated peer reviews from human-written ones by analyzing …
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LLMs show promise for patient inquiry triage, but not autonomous deployment
Researchers have explored the use of few-shot large language models for categorizing online patient inquiries, aiming to improve clinical triage. They compared prompted LLMs against traditional methods like TF-IDF and B…
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Hybrid model achieves strong Indonesian sentiment analysis results
Researchers have developed a hybrid approach for Indonesian sentiment analysis, combining TF-IDF text features with logistic regression and a neural network baseline. The study focused on classifying social media text i…
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New defense framework tackles multilingual prompt injection attacks
Researchers have developed MIPIAD, a defense framework to combat indirect prompt injection attacks in multilingual large language model systems. The framework combines a Qwen2.5-1.5B model fine-tuned with LoRA, TF-IDF l…
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XGBoost algorithm predicts e-commerce customer satisfaction from YouTube comments
This research paper introduces a predictive model for customer satisfaction using the XGBoost algorithm and TF-IDF vectorization on YouTube comments from Indonesian e-commerce review videos. The study found that the PyC…
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CNN-BiLSTM outperforms AutoML for Indonesian Twitter hate speech detection
This paper compares PyCaret AutoML and a CNN-BiLSTM model for detecting hate speech on Indonesian Twitter. The CNN-BiLSTM model achieved superior performance, with an accuracy of 83.8% and an F1-score of 81.2%, outperfo…
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Researchers use BiLSTM with attention to improve game review sentiment analysis
Researchers have developed an attention-based Bidirectional Long Short-Term Memory (BiLSTM) model to improve sentiment classification of Steam game reviews. This deep learning approach, implemented in PyTorch, was train…
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Hungarian student essays automatically classified for reflection levels using ML
Researchers have developed a system for automatically classifying reflection levels in Hungarian student essays, addressing a gap in automated analysis for the language. The study utilized a dataset of 1,954 essays, exp…
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Indonesian students show positive sentiment towards AI in higher education
A new study analyzed Indonesian student sentiment regarding AI adoption in higher education, comparing traditional machine learning with Transformer-based deep learning models. The research utilized a dataset of 2,295 l…
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Study compares AutoML and BiLSTM for Indonesian Instagram cyberbullying detection
This research paper compares automated machine learning (AutoML) and Bidirectional Long Short-Term Memory (BiLSTM) models for detecting cyberbullying in Indonesian Instagram comments. The study utilized a dataset of 650…
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LLMs boost recipe nutrient accuracy but increase inference time, study finds
A new paper compares traditional methods with large language models (LLMs) for estimating nutrient content from recipes. The study found that while LLMs like Gemini 2.5 Flash, especially in a hybrid approach with TF-IDF…
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Studies benchmark AutoML and BiLSTM for NLP tasks, showing mixed results
Researchers have compared traditional machine learning methods with deep learning models for various natural language processing tasks, including fine-grained emotion classification and sentiment analysis. Studies utili…