{"total":30,"rows":[{"id":"2112.07577","title":"GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval","created":"2021-12-14","cited_by_count":119,"area":null},{"id":"2206.08009","title":"Balancing Discriminability and Transferability for Source-Free Domain Adaptation","created":"2022-06-16","cited_by_count":58,"area":null},{"id":"2202.04824","title":"AdaPrompt: Adaptive Model Training for Prompt-based NLP","created":"2022-02-10","cited_by_count":30,"area":null},{"id":"2211.03154","title":"On the Domain Adaptation and Generalization of Pretrained Language Models: A Survey","created":"2022-11-06","cited_by_count":23,"area":null},{"id":"2210.15212","title":"COCO-DR: Combating Distribution Shifts in Zero-Shot Dense Retrieval with Contrastive and Distributionally Robust Learning","created":"2022-10-27","cited_by_count":20,"area":null},{"id":"2111.00667","title":"Unsupervised Domain Adaptation with Adapter","created":"2021-11-01","cited_by_count":14,"area":null},{"id":"2208.03197","title":"Low-Resource Dense Retrieval for Open-Domain Question Answering: A Comprehensive Survey","created":"2022-08-05","cited_by_count":14,"area":null},{"id":"2302.03194","title":"UDApter -- Efficient Domain Adaptation Using Adapters","created":"2023-02-07","cited_by_count":13,"area":null},{"id":"2310.10191","title":"VIBE: Topic-Driven Temporal Adaptation for Twitter Classification","created":"2023-10-16","cited_by_count":12,"area":null},{"id":"2302.04618","title":"Robust Question Answering against Distribution Shifts with Test-Time Adaptation: An Empirical Study","created":"2023-02-09","cited_by_count":8,"area":null},{"id":"2301.00304","title":"Sample-Efficient Unsupervised Domain Adaptation of Speech Recognition Systems A case study for Modern Greek","created":"2022-12-31","cited_by_count":7,"area":null},{"id":"2406.00606","title":"LLMs Could Autonomously Learn Without External Supervision","created":"2024-06-02","cited_by_count":6,"area":null},{"id":"2307.00963","title":"Challenges in Domain-Specific Abstractive Summarization and How to Overcome them","created":"2023-07-03","cited_by_count":5,"area":null},{"id":"2401.17514","title":"How Useful is Continued Pre-Training for Generative Unsupervised Domain Adaptation?","created":"2024-01-31","cited_by_count":5,"area":null},{"id":"2110.09454","title":"SentimentArcs: A Novel Method for Self-Supervised Sentiment Analysis of Time Series Shows SOTA Transformers Can Struggle Finding Narrative Arcs","created":"2021-10-18","cited_by_count":4,"area":null},{"id":"2207.04564","title":"Domain Confused Contrastive Learning for Unsupervised Domain Adaptation","created":"2022-07-10","cited_by_count":4,"area":null},{"id":"2310.16959","title":"Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning","created":"2023-10-25","cited_by_count":4,"area":null},{"id":"2304.09820","title":"A Two-Stage Framework with Self-Supervised Distillation For Cross-Domain Text Classification","created":"2023-04-18","cited_by_count":3,"area":null},{"id":"2209.09485","title":"Generalizing through Forgetting -- Domain Generalization for Symptom Event Extraction in Clinical Notes","created":"2022-09-20","cited_by_count":2,"area":null},{"id":"2211.03988","title":"Unsupervised Domain Adaptation for Sparse Retrieval by Filling Vocabulary and Word Frequency Gaps","created":"2022-11-08","cited_by_count":2,"area":null},{"id":"2212.03760","title":"Pivotal Role of Language Modeling in Recommender Systems: Enriching Task-specific and Task-agnostic Representation Learning","created":"2022-12-07","cited_by_count":2,"area":null},{"id":"2310.14849","title":"Universal Domain Adaptation for Robust Handling of Distributional Shifts in NLP","created":"2023-10-23","cited_by_count":2,"area":null},{"id":"2312.17263","title":"TACIT: A Target-Agnostic Feature Disentanglement Framework for Cross-Domain Text Classification","created":"2023-12-25","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":"2205.04050","title":"Few-shot Mining of Naturally Occurring Inputs and Outputs","created":"2022-05-09","cited_by_count":1,"area":null},{"id":"2402.12627","title":"A Comprehensive Review of Machine Learning Advances on Data Change: A Cross-Field Perspective","created":"2024-02-20","cited_by_count":1,"area":null},{"id":"2505.24656","title":"MSDA: Combining Pseudo-labeling and Self-Supervision for Unsupervised Domain Adaptation in ASR","created":"2025-05-30","cited_by_count":1,"area":null},{"id":"2406.15490","title":"Causal Discovery Inspired Unsupervised Domain Adaptation for Emotion-Cause Pair Extraction","created":"2024-06-18","cited_by_count":0,"area":null},{"id":"2503.05281","title":"Similarity-Based Domain Adaptation with LLMs","created":"2025-03-07","cited_by_count":0,"area":null},{"id":"2606.22272","title":"MixedPEFT: Combining Multiple PEFT Methods with Mixed Objectives for Unsupervised Domain Adaptation","created":"2026-06-20","cited_by_count":0,"area":null}],"next_cursor":null}