{"total":43,"rows":[{"id":"2212.03827","title":"Discovering Latent Knowledge in Language Models Without Supervision","created":"2022-12-07","cited_by_count":767,"area":null},{"id":"2106.04489","title":"Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks","created":"2021-06-08","cited_by_count":284,"area":null},{"id":"2201.05966","title":"UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models","created":"2022-01-16","cited_by_count":231,"area":null},{"id":"2202.04538","title":"Generating Training Data with Language Models: Towards Zero-Shot Language Understanding","created":"2022-02-09","cited_by_count":199,"area":null},{"id":"2104.08835","title":"CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP","created":"2021-04-18","cited_by_count":142,"area":null},{"id":"2104.14690","title":"Entailment as Few-Shot Learner","created":"2021-04-29","cited_by_count":123,"area":null},{"id":"2108.13161","title":"Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners","created":"2021-08-30","cited_by_count":115,"area":null},{"id":"2210.03050","title":"State-of-the-art generalisation research in NLP: A taxonomy and review","created":"2022-10-06","cited_by_count":98,"area":null},{"id":"2109.03659","title":"Label Verbalization and Entailment for Effective Zero- and Few-Shot Relation Extraction","created":"2021-09-08","cited_by_count":73,"area":null},{"id":"2205.01703","title":"Improving In-Context Few-Shot Learning via Self-Supervised Training","created":"2022-05-03","cited_by_count":57,"area":null},{"id":"2109.03630","title":"Discrete and Soft Prompting for Multilingual Models","created":"2021-09-08","cited_by_count":49,"area":null},{"id":"2104.08731","title":"Can NLI Models Verify QA Systems' Predictions?","created":"2021-04-18","cited_by_count":46,"area":null},{"id":"2109.12575","title":"Paradigm Shift in Natural Language Processing","created":"2021-09-26","cited_by_count":39,"area":null},{"id":"2205.09837","title":"Summarization as Indirect Supervision for Relation Extraction","created":"2022-05-19","cited_by_count":31,"area":null},{"id":"2104.11882","title":"Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System","created":"2021-04-24","cited_by_count":30,"area":null},{"id":"2205.01376","title":"Textual Entailment for Event Argument Extraction: Zero- and Few-Shot with Multi-Source Learning","created":"2022-05-03","cited_by_count":25,"area":null},{"id":"2201.11332","title":"Ontology-enhanced Prompt-tuning for Few-shot Learning","created":"2022-01-27","cited_by_count":24,"area":null},{"id":"2312.17543","title":"Building Efficient Universal Classifiers with Natural Language Inference","created":"2023-12-29","cited_by_count":22,"area":null},{"id":"2202.06167","title":"Ultra-fine Entity Typing with Indirect Supervision from Natural Language Inference","created":"2022-02-12","cited_by_count":17,"area":null},{"id":"2203.14655","title":"Few-Shot Learning with Siamese Networks and Label Tuning","created":"2022-03-28","cited_by_count":15,"area":null},{"id":"2209.15373","title":"PART: Pre-trained Authorship Representation Transformer","created":"2022-09-30","cited_by_count":13,"area":null},{"id":"2212.10784","title":"Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?","created":"2022-12-21","cited_by_count":13,"area":null},{"id":"2204.09347","title":"Active Few-Shot Learning with FASL","created":"2022-04-20","cited_by_count":11,"area":null},{"id":"2111.01322","title":"Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP","created":"2021-11-02","cited_by_count":10,"area":null},{"id":"2111.02570","title":"CLUES: Few-Shot Learning Evaluation in Natural Language Understanding","created":"2021-11-04","cited_by_count":9,"area":null},{"id":"2112.07522","title":"LMTurk: Few-Shot Learners as Crowdsourcing Workers in a Language-Model-as-a-Service Framework","created":"2021-12-14","cited_by_count":9,"area":null},{"id":"2211.06607","title":"Few-shot Multimodal Sentiment Analysis based on Multimodal Probabilistic Fusion Prompts","created":"2022-11-12","cited_by_count":9,"area":null},{"id":"2302.03353","title":"What do Language Models know about word senses? Zero-Shot WSD with Language Models and Domain Inventories","created":"2023-02-07","cited_by_count":9,"area":null},{"id":"2306.11066","title":"Adversarial Robustness of Prompt-based Few-Shot Learning for Natural Language Understanding","created":"2023-06-19","cited_by_count":8,"area":null},{"id":"2307.02729","title":"Text Alignment Is An Efficient Unified Model for Massive NLP Tasks","created":"2023-07-06","cited_by_count":8,"area":null},{"id":"2210.14299","title":"OpenStance: Real-world Zero-shot Stance Detection","created":"2022-10-25","cited_by_count":7,"area":null},{"id":"2210.06720","title":"LIME: Weakly-Supervised Text Classification Without Seeds","created":"2022-10-13","cited_by_count":6,"area":null},{"id":"2202.01924","title":"Zero-Shot Aspect-Based Sentiment Analysis","created":"2022-02-04","cited_by_count":5,"area":null},{"id":"2206.10914","title":"Template-based Approach to Zero-shot Intent Recognition","created":"2022-06-22","cited_by_count":5,"area":null},{"id":"2204.10543","title":"Zero and Few-shot Learning for Author Profiling","created":"2022-04-22","cited_by_count":4,"area":null},{"id":"2212.00301","title":"Learning to Select from Multiple Options","created":"2022-12-01","cited_by_count":4,"area":null},{"id":"2204.09481","title":"Unsupervised Ranking and Aggregation of Label Descriptions for Zero-Shot Classifiers","created":"2022-04-20","cited_by_count":1,"area":null},{"id":"2209.02276","title":"Zero-shot Aspect-level Sentiment Classification via Explicit Utilization of Aspect-to-Document Sentiment Composition","created":"2022-09-06","cited_by_count":1,"area":null},{"id":"2112.07434","title":"Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent Detection","created":"2021-12-14","cited_by_count":0,"area":null},{"id":"2202.03120","title":"To Tune or Not To Tune? Zero-shot Models for Legal Case Entailment","created":"2022-02-07","cited_by_count":0,"area":null},{"id":"2208.10126","title":"Revising Image-Text Retrieval via Multi-Modal Entailment","created":"2022-08-22","cited_by_count":0,"area":null},{"id":"2210.07587","title":"ConEntail: An Entailment-based Framework for Universal Zero and Few Shot Classification with Supervised Contrastive Pretraining","created":"2022-10-14","cited_by_count":0,"area":null},{"id":"2210.15225","title":"BERT-Flow-VAE: A Weakly-supervised Model for Multi-Label Text Classification","created":"2022-10-27","cited_by_count":0,"area":null}],"next_cursor":null}