{"total":35,"rows":[{"id":"2211.13445","title":"Delving into Out-of-Distribution Detection with Vision-Language Representations","created":"2022-11-24","cited_by_count":216,"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":"2407.03282","title":"LLM Internal States Reveal Hallucination Risk Faced With a Query","created":"2024-07-03","cited_by_count":82,"area":null},{"id":"2109.06827","title":"Types of Out-of-Distribution Texts and How to Detect Them","created":"2021-09-14","cited_by_count":80,"area":null},{"id":"2104.08812","title":"Contrastive Out-of-Distribution Detection for Pretrained Transformers","created":"2021-04-18","cited_by_count":71,"area":null},{"id":"2101.03778","title":"Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection","created":"2021-01-11","cited_by_count":70,"area":null},{"id":"2306.04459","title":"Uncertainty in Natural Language Processing: Sources, Quantification, and Applications","created":"2023-06-05","cited_by_count":44,"area":null},{"id":"2106.08616","title":"Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training","created":"2021-06-16","cited_by_count":42,"area":null},{"id":"2305.03236","title":"A Survey on Out-of-Distribution Detection in NLP","created":"2023-05-05","cited_by_count":31,"area":null},{"id":"2305.13282","title":"Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection","created":"2023-05-22","cited_by_count":29,"area":null},{"id":"2104.08481","title":"Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes","created":"2021-04-17","cited_by_count":27,"area":null},{"id":"2205.01500","title":"Meta Learning for Natural Language Processing: A Survey","created":"2022-05-03","cited_by_count":26,"area":null},{"id":"2210.15452","title":"Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity","created":"2022-10-20","cited_by_count":25,"area":null},{"id":"2106.14464","title":"Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU","created":"2021-06-28","cited_by_count":22,"area":null},{"id":"2109.03079","title":"GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentation","created":"2021-09-07","cited_by_count":20,"area":null},{"id":"2203.11396","title":"Towards Textual Out-of-Domain Detection without In-Domain Labels","created":"2022-03-22","cited_by_count":14,"area":null},{"id":"2207.13211","title":"A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog","created":"2022-07-26","cited_by_count":14,"area":null},{"id":"2211.05561","title":"Estimating Soft Labels for Out-of-Domain Intent Detection","created":"2022-11-10","cited_by_count":11,"area":null},{"id":"2406.12629","title":"SeTAR: Out-of-Distribution Detection with Selective Low-Rank Approximation","created":"2024-06-18","cited_by_count":10,"area":null},{"id":"2109.07968","title":"Alquist 4.0: Towards Social Intelligence Using Generative Models and Dialogue Personalization","created":"2021-09-16","cited_by_count":9,"area":null},{"id":"2304.11058","title":"Novel Intent Detection and Active Learning Based Classification (Student Abstract)","created":"2023-02-22","cited_by_count":6,"area":null},{"id":"2305.03237","title":"Out-of-Domain Intent Detection Considering Multi-Turn Dialogue Contexts","created":"2023-05-05","cited_by_count":6,"area":null},{"id":"2204.07804","title":"Learning to Classify Open Intent via Soft Labeling and Manifold Mixup","created":"2022-04-16","cited_by_count":5,"area":null},{"id":"2409.03203","title":"An Effective Deployment of Diffusion LM for Data Augmentation in Low-Resource Sentiment Classification","created":"2024-09-05","cited_by_count":5,"area":null},{"id":"2108.12229","title":"ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection","created":"2021-08-27","cited_by_count":4,"area":null},{"id":"2308.02746","title":"Meta-Tsallis-Entropy Minimization: A New Self-Training Approach for Domain Adaptation on Text Classification","created":"2023-08-04","cited_by_count":4,"area":null},{"id":"2101.07942","title":"Towards Confident Machine Reading Comprehension","created":"2021-01-20","cited_by_count":3,"area":null},{"id":"2205.02005","title":"A Framework to Generate High-Quality Datapoints for Multiple Novel Intent Detection","created":"2022-05-04","cited_by_count":2,"area":null},{"id":"2404.01785","title":"Can Humans Identify Domains?","created":"2024-04-02","cited_by_count":2,"area":null},{"id":"2205.09021","title":"Exploring the Advantages of Dense-Vector to One-Hot Encoding of Intent Classes in Out-of-Scope Detection Tasks","created":"2022-05-18","cited_by_count":1,"area":null},{"id":"2305.18026","title":"Semantic Role Labeling Guided Out-of-distribution Detection","created":"2023-05-29","cited_by_count":1,"area":null},{"id":"2306.08852","title":"BED: Bi-Encoder-Based Detectors for Out-of-Distribution Detection","created":"2023-06-15","cited_by_count":0,"area":null},{"id":"2502.11113","title":"Valuable Hallucinations: Realizable Non-realistic Propositions","created":"2025-02-16","cited_by_count":0,"area":null},{"id":"2511.05921","title":"IDALC: A Semi-Supervised Framework for Intent Detection and Active Learning based Correction","created":"2025-11-08","cited_by_count":0,"area":null},{"id":"2601.11700","title":"Telling Human and Machine Handwriting Apart","created":"2026-01-16","cited_by_count":0,"area":null}],"next_cursor":null}