Papers Binary text classification
“Binary text classification” 태그가 달린 논문 20편 · 필터 해제
Reliable Decision Support with LLMs: A Framework for Evaluating Consistency in Binary Text Classification Applications
This study introduces a framework for evaluating consistency in large language model (LLM) binary text classification, addressing the lack of established reliability assessment methods. Adapting psychometric principles, …
ArticlesBinary text classificationLarge Language ModelSentiment Analysis+3GigaCheck: Detecting LLM-generated Content
With the increasing quality and spread of LLM-based assistants, the amount of LLM-generated content is growing rapidly. In many cases and tasks, such texts are already indistinguishable from those written by humans, and …
Binary text classificationBoundary DetectionLLM-generated Text DetectionText Classification+1Calibrated Large Language Models for Binary Question Answering
Quantifying the uncertainty of predictions made by large language models (LLMs) in binary text classification tasks remains a challenge. Calibration, in the context of LLMs, refers to the alignment between the model's pr…
Binary text classificationQuestion Answeringtext-classificationText ClassificationHoaxpedia: A Unified Wikipedia Hoax Articles Dataset
Hoaxes are a recognised form of disinformation created deliberately, with potential serious implications in the credibility of reference knowledge resources such as Wikipedia. What makes detecting Wikipedia hoaxes hard i…
ArticlesBinary ClassificationBinary text classificationtext-classification+1LLM-as-a-Coauthor: Can Mixed Human-Written and Machine-Generated Text Be Detected?
With the rapid development and widespread application of Large Language Models (LLMs), the use of Machine-Generated Text (MGT) has become increasingly common, bringing with it potential risks, especially in terms of qual…
Binary text classificationIdentification of the Relevance of Comments in Codes Using Bag of Words and Transformer Based Models
The Forum for Information Retrieval (FIRE) started a shared task this year for classification of comments of different code segments. This is binary text classification task where the objective is to identify whether com…
Binary text classificationFeature EngineeringInformation Retrievaltext-classification+1DACCORD : un jeu de données pour la Détection Automatique d'énonCés COntRaDictoires en français
La tâche de détection automatique de contradictions logiques entre énoncés en TALN est une tâche de classification binaire, où chaque paire de phrases reçoit une étiquette selon que les deux phrases se contredisent ou no…
Binary ClassificationBinary text classificationSentenceSentence-Pair Classification+1Ghostbuster: Detecting Text Ghostwritten by Large Language Models
We introduce Ghostbuster, a state-of-the-art system for detecting AI-generated text. Our method works by passing documents through a series of weaker language models, running a structured search over possible combination…
ArticlesBinary text classificationMAGE: Machine-generated Text Detection in the Wild
Large language models (LLMs) have achieved human-level text generation, emphasizing the need for effective AI-generated text detection to mitigate risks like the spread of fake news and plagiarism. Existing research has …
Binary text classificationFace SwappingStory GenerationText Detection+1Analyzing the Generalizability of Deep Contextualized Language Representations For Text Classification
This study evaluates the robustness of two state-of-the-art deep contextual language representations, ELMo and DistilBERT, on supervised learning of binary protest news classification and sentiment analysis of product re…
Binary text classificationNews ClassificationSentiment Analysistext-classification+1Argumentative Explanations for Pattern-Based Text Classifiers
Recent works in Explainable AI mostly address the transparency issue of black-box models or create explanations for any kind of models (i.e., they are model-agnostic), while leaving explanations of interpretable models l…
Binary text classificationregressionSpecificitytext-classification+1TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
Recent progress in generative language models has enabled machines to generate astonishingly realistic texts. While there are many legitimate applications of such models, there is also a rising need to distinguish machin…
Authorship AttributionBinary text classificationFake News DetectionText GenerationActive Learning for BERT: An Empirical Study
Real world scenarios present a challenge for text classification, since labels are usually expensive and the data is often characterized by class imbalance. Active Learning (AL) is a ubiquitous paradigm to cope with data…
Active LearningBinary text classificationClassificationGeneral Classification+2CIA_NITT at WNUT-2020 Task 2: Classification of COVID-19 Tweets Using Pre-trained Language Models
This paper presents our models for WNUT 2020 shared task2. The shared task2 involves identification of COVID-19 related informative tweets. We treat this as binary text classification problem and experiment with pre-trai…
Binary text classificationTask 2text-classificationText ClassificationTweepFake: about Detecting Deepfake Tweets
The recent advances in language modeling significantly improved the generative capabilities of deep neural models: in 2019 OpenAI released GPT-2, a pre-trained language model that can autonomously generate coherent, non-…
Binary text classificationDeepFake DetectionFace SwappingLanguage Modeling+3Evaluating shallow and deep learning strategies for the 2018 n2c2 shared task on clinical text classification
Objective: Automated clinical phenotyping is challenging because word-based features quickly turn it into a high-dimensional problem, in which the small, privacy-restricted, training datasets might lead to overfitting. P…
BIG-bench Machine LearningBinary text classificationDeep LearningGeneral Classification+5Neural Legal Judgment Prediction in English
Legal judgment prediction is the task of automatically predicting the outcome of a court case, given a text describing the case's facts. Previous work on using neural models for this task has focused on Chinese; only fea…
Binary text classificationGeneral ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+1Learning Representations for Soft Skill Matching
Employers actively look for talents having not only specific hard skills but also various soft skills. To analyze the soft skill demands on the job market, it is important to be able to detect soft skill phrases from job…
Binary text classificationtext-classificationText ClassificationDeception Detection for the Russian Language: Lexical and Syntactic Parameters
The field of automated deception detection in written texts is methodologically challenging. Different linguistic levels (lexics, syntax and semantics) are basically used for different types of English texts to reveal if…
Binary text classificationDeception DetectionInformation RetrievalPOS+2Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights
Multilayer Neural Networks (MNNs) are commonly trained using gradient descent-based methods, such as BackPropagation (BP). Inference in probabilistic graphical models is often done using variational Bayes methods, such a…
Binary text classificationtext-classificationText Classification