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1909.00161
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Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach
31 August 2019
Wenpeng Yin
Jamaal Hay
Dan Roth
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Papers citing
"Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach"
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The ACL OCL Corpus: Advancing Open Science in Computational Linguistics
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PESCO: Prompt-enhanced Self Contrastive Learning for Zero-shot Text Classification
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EXnet: Efficient In-context Learning for Data-less Text classification
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A Benchmark on Extremely Weakly Supervised Text Classification: Reconcile Seed Matching and Prompting Approaches
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Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models
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Artem Abzaliev
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Siqi Shen
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Zero-Shot Text Classification via Self-Supervised Tuning
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ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval
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Chao Zhang
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43
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ZARA: Improving Few-Shot Self-Rationalization for Small Language Models
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Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good
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Low-Resource Multi-Granularity Academic Function Recognition Based on Multiple Prompt Knowledge
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38
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Psychologically-Inspired Causal Prompts
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Sentence-Level Relation Extraction via Contrastive Learning with Descriptive Relation Prompts
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46
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Simple Yet Effective Synthetic Dataset Construction for Unsupervised Opinion Summarization
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Large Language Model Instruction Following: A Survey of Progresses and Challenges
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Logic Against Bias: Textual Entailment Mitigates Stereotypical Sentence Reasoning
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QAID: Question Answering Inspired Few-shot Intent Detection
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Boaz Carmeli
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Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents
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LabelPrompt: Effective Prompt-based Learning for Relation Classification
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Flexible, Model-Agnostic Method for Materials Data Extraction from Text Using General Purpose Language Models
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52
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48
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Automated Identification of Eviction Status from Electronic Health Record Notes
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47
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Legal Prompt Engineering for Multilingual Legal Judgement Prediction
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Learning to Select from Multiple Options
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55
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Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches
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56
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