{"total":31,"rows":[{"id":"2107.07170","title":"FLEX: Unifying Evaluation for Few-Shot NLP","created":"2021-07-15","cited_by_count":67,"area":null},{"id":"2102.01335","title":"Neural Data Augmentation via Example Extrapolation","created":"2021-02-02","cited_by_count":54,"area":null},{"id":"2104.05763","title":"Few-shot Intent Classification and Slot Filling with Retrieved Examples","created":"2021-04-12","cited_by_count":35,"area":null},{"id":"2110.08458","title":"Controllable Semantic Parsing via Retrieval Augmentation","created":"2021-10-16","cited_by_count":35,"area":null},{"id":"2204.07128","title":"Label Semantic Aware Pre-training for Few-shot Text Classification","created":"2022-04-14","cited_by_count":18,"area":null},{"id":"2205.13568","title":"Learning Dialogue Representations from Consecutive Utterances","created":"2022-05-26","cited_by_count":17,"area":null},{"id":"2101.06514","title":"Linguistically-Enriched and Context-Aware Zero-shot Slot Filling","created":"2021-01-16","cited_by_count":12,"area":null},{"id":"2110.13691","title":"An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling","created":"2021-10-26","cited_by_count":9,"area":null},{"id":"2204.13021","title":"NLU++: A Multi-Label, Slot-Rich, Generalisable Dataset for Natural Language Understanding in Task-Oriented Dialogue","created":"2022-04-27","cited_by_count":8,"area":null},{"id":"2309.08827","title":"S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs","created":"2023-09-16","cited_by_count":7,"area":null},{"id":"2412.08587","title":"Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning","created":"2024-12-11","cited_by_count":7,"area":null},{"id":"2106.07343","title":"Learning to Bridge Metric Spaces: Few-shot Joint Learning of Intent Detection and Slot Filling","created":"2021-05-25","cited_by_count":6,"area":null},{"id":"2305.14827","title":"Pre-training Intent-Aware Encoders for Zero- and Few-Shot Intent Classification","created":"2023-05-24","cited_by_count":5,"area":null},{"id":"2403.17536","title":"ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot Filler","created":"2024-03-26","cited_by_count":5,"area":null},{"id":"2108.11635","title":"MCML: A Novel Memory-based Contrastive Meta-Learning Method for Few Shot Slot Tagging","created":"2021-08-26","cited_by_count":4,"area":null},{"id":"2305.13528","title":"Transfer-Free Data-Efficient Multilingual Slot Labeling","created":"2023-05-22","cited_by_count":4,"area":null},{"id":"2106.15986","title":"Cross-lingual alignments of ELMo contextual embeddings","created":"2021-06-30","cited_by_count":3,"area":null},{"id":"2109.08754","title":"Semi-Supervised Few-Shot Intent Classification and Slot Filling","created":"2021-09-17","cited_by_count":3,"area":null},{"id":"2206.07841","title":"TOKEN is a MASK: Few-shot Named Entity Recognition with Pre-trained Language Models","created":"2022-06-15","cited_by_count":2,"area":null},{"id":"2210.06440","title":"The Devil is in the Details: On Models and Training Regimes for Few-Shot Intent Classification","created":"2022-10-12","cited_by_count":2,"area":null},{"id":"2303.13801","title":"Toward Open-domain Slot Filling via Self-supervised Co-training","created":"2023-03-24","cited_by_count":2,"area":null},{"id":"2305.03793","title":"Towards Zero-Shot Frame Semantic Parsing with Task Agnostic Ontologies and Simple Labels","created":"2023-05-05","cited_by_count":2,"area":null},{"id":"2312.13495","title":"Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling","created":"2023-12-21","cited_by_count":2,"area":null},{"id":"2111.12421","title":"Few-shot Named Entity Recognition with Cloze Questions","created":"2021-11-24","cited_by_count":1,"area":null},{"id":"2112.04999","title":"Few-Shot NLU with Vector Projection Distance and Abstract Triangular CRF","created":"2021-12-09","cited_by_count":1,"area":null},{"id":"2204.04952","title":"MGIMN: Multi-Grained Interactive Matching Network for Few-shot Text Classification","created":"2022-04-11","cited_by_count":1,"area":null},{"id":"2303.05034","title":"Multi-Stage Coarse-to-Fine Contrastive Learning for Conversation Intent Induction","created":"2023-03-09","cited_by_count":1,"area":null},{"id":"2305.14299","title":"Template-assisted Contrastive Learning of Task-oriented Dialogue Sentence Embeddings","created":"2023-05-23","cited_by_count":1,"area":null},{"id":"2309.03877","title":"Introducing \"Forecast Utterance\" for Conversational Data Science","created":"2023-09-07","cited_by_count":1,"area":null},{"id":"2101.08091","title":"A survey of joint intent detection and slot-filling models in natural language understanding","created":"2021-01-20","cited_by_count":0,"area":null},{"id":"2212.10728","title":"Spoken Language Understanding for Conversational AI: Recent Advances and Future Direction","created":"2022-12-21","cited_by_count":0,"area":null}],"next_cursor":null}