{"total":147,"rows":[{"id":"2107.13586","title":"Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing","created":"2021-07-28","cited_by_count":2234,"area":null},{"id":"2111.01243","title":"Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey","created":"2021-11-01","cited_by_count":463,"area":null},{"id":"2212.09689","title":"Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor","created":"2022-12-19","cited_by_count":397,"area":null},{"id":"2208.03274","title":"A Holistic Approach to Undesired Content Detection in the Real World","created":"2022-08-05","cited_by_count":356,"area":null},{"id":"2401.00368","title":"Improving Text Embeddings with Large Language Models","created":"2023-12-31","cited_by_count":303,"area":null},{"id":"2306.15895","title":"Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias","created":"2023-06-28","cited_by_count":232,"area":null},{"id":"2202.07922","title":"ZeroGen: Efficient Zero-shot Learning via Dataset Generation","created":"2022-02-16","cited_by_count":211,"area":null},{"id":"2202.08904","title":"SGPT: GPT Sentence Embeddings for Semantic Search","created":"2022-02-17","cited_by_count":204,"area":null},{"id":"2201.05955","title":"WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation","created":"2022-01-16","cited_by_count":202,"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":"2306.00622","title":"ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing","created":"2023-06-01","cited_by_count":122,"area":null},{"id":"2303.04132","title":"Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction","created":"2023-03-07","cited_by_count":89,"area":null},{"id":"2304.14293","title":"Controlled Text Generation with Natural Language Instructions","created":"2023-04-27","cited_by_count":87,"area":null},{"id":"2202.13047","title":"AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation","created":"2022-02-26","cited_by_count":79,"area":null},{"id":"2310.19596","title":"LLMaAA: Making Large Language Models as Active Annotators","created":"2023-10-30","cited_by_count":79,"area":null},{"id":"2207.14502","title":"Language Models Can Teach Themselves to Program Better","created":"2022-07-29","cited_by_count":78,"area":null},{"id":"2109.04650","title":"What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers","created":"2021-09-10","cited_by_count":76,"area":null},{"id":"2210.13918","title":"Differentially Private Language Models for Secure Data Sharing","created":"2022-10-25","cited_by_count":68,"area":null},{"id":"2210.12329","title":"ProGen: Progressive Zero-shot Dataset Generation via In-context Feedback","created":"2022-10-22","cited_by_count":67,"area":null},{"id":"2202.05144","title":"InPars: Data Augmentation for Information Retrieval using Large Language Models","created":"2022-02-10","cited_by_count":62,"area":null},{"id":"2210.14140","title":"Contrastive Search Is What You Need For Neural Text Generation","created":"2022-10-25","cited_by_count":59,"area":null},{"id":"2205.12696","title":"Revisiting DocRED -- Addressing the False Negative Problem in Relation Extraction","created":"2022-05-25","cited_by_count":57,"area":null},{"id":"2311.17404","title":"VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models","created":"2023-11-29","cited_by_count":55,"area":null},{"id":"2201.06910","title":"ZeroPrompt: Scaling Prompt-Based Pretraining to 1,000 Tasks Improves Zero-Shot Generalization","created":"2022-01-18","cited_by_count":54,"area":null},{"id":"2203.12942","title":"Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets","created":"2022-03-24","cited_by_count":54,"area":null},{"id":"2301.08881","title":"Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness","created":"2023-01-21","cited_by_count":53,"area":null},{"id":"2205.02318","title":"Language Models in the Loop: Incorporating Prompting into Weak Supervision","created":"2022-05-04","cited_by_count":52,"area":null},{"id":"2308.12060","title":"FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering","created":"2023-08-23","cited_by_count":51,"area":null},{"id":"2205.12679","title":"Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning","created":"2022-05-25","cited_by_count":50,"area":null},{"id":"2404.10859","title":"Forcing Diffuse Distributions out of Language Models","created":"2024-04-16","cited_by_count":48,"area":null},{"id":"2304.08460","title":"LongForm: Effective Instruction Tuning with Reverse Instructions","created":"2023-04-17","cited_by_count":47,"area":null},{"id":"2312.10007","title":"Faithful Persona-based Conversational Dataset Generation with Large Language Models","created":"2023-12-15","cited_by_count":47,"area":null},{"id":"2312.08361","title":"Distributed Inference and Fine-tuning of Large Language Models Over The Internet","created":"2023-12-13","cited_by_count":42,"area":null},{"id":"2111.13440","title":"True Few-Shot Learning with Prompts -- A Real-World Perspective","created":"2021-11-26","cited_by_count":38,"area":null},{"id":"2210.17041","title":"GPS: Genetic Prompt Search for Efficient Few-shot Learning","created":"2022-10-31","cited_by_count":37,"area":null},{"id":"2406.11149","title":"GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory","created":"2024-06-17","cited_by_count":37,"area":null},{"id":"2408.02373","title":"Operationalizing Contextual Integrity in Privacy-Conscious Assistants","created":"2024-08-05","cited_by_count":37,"area":null},{"id":"2211.03044","title":"Tuning Language Models as Training Data Generators for Augmentation-Enhanced Few-Shot Learning","created":"2022-11-06","cited_by_count":36,"area":null},{"id":"2312.02614","title":"Prompt Optimization via Adversarial In-Context Learning","created":"2023-12-05","cited_by_count":33,"area":null},{"id":"2212.10408","title":"Geographic and Geopolitical Biases of Language Models","created":"2022-12-20","cited_by_count":29,"area":null},{"id":"2310.03269","title":"InstructProtein: Aligning Human and Protein Language via Knowledge Instruction","created":"2023-10-05","cited_by_count":28,"area":null},{"id":"2305.10703","title":"ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval","created":"2023-05-18","cited_by_count":26,"area":null},{"id":"2109.10126","title":"ConvFiT: Conversational Fine-Tuning of Pretrained Language Models","created":"2021-09-21","cited_by_count":25,"area":null},{"id":"2310.19975","title":"BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing","created":"2023-10-30","cited_by_count":25,"area":null},{"id":"2110.05448","title":"Unsupervised Neural Machine Translation with Generative Language Models Only","created":"2021-10-11","cited_by_count":24,"area":null},{"id":"2210.14552","title":"A Robust Bias Mitigation Procedure Based on the Stereotype Content Model","created":"2022-10-26","cited_by_count":24,"area":null},{"id":"2305.15077","title":"Contrastive Learning of Sentence Embeddings from Scratch","created":"2023-05-24","cited_by_count":24,"area":null},{"id":"2312.02073","title":"A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepedia","created":"2023-12-04","cited_by_count":24,"area":null},{"id":"2210.07074","title":"CLASP: Few-Shot Cross-Lingual Data Augmentation for Semantic Parsing","created":"2022-10-13","cited_by_count":21,"area":null},{"id":"2408.12503","title":"The Russian-focused embedders' exploration: ruMTEB benchmark and Russian embedding model design","created":"2024-08-22","cited_by_count":20,"area":null},{"id":"2210.16798","title":"Generate, Discriminate and Contrast: A Semi-Supervised Sentence Representation Learning Framework","created":"2022-10-30","cited_by_count":19,"area":null},{"id":"2310.17876","title":"TarGEN: Targeted Data Generation with Large Language Models","created":"2023-10-27","cited_by_count":17,"area":null},{"id":"2404.10229","title":"Generative Text Steganography with Large Language Model","created":"2024-04-16","cited_by_count":17,"area":null},{"id":"2310.16263","title":"Enhancing Large Language Models for Secure Code Generation: A Dataset-driven Study on Vulnerability Mitigation","created":"2023-10-25","cited_by_count":15,"area":null},{"id":"2301.02998","title":"InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers","created":"2023-01-08","cited_by_count":14,"area":null},{"id":"2305.14926","title":"Universal Self-Adaptive Prompting","created":"2023-05-24","cited_by_count":14,"area":null},{"id":"2403.11395","title":"Automated data processing and feature engineering for deep learning and big data applications: a survey","created":"2024-03-18","cited_by_count":14,"area":null},{"id":"2210.14803","title":"Don't Prompt, Search! Mining-based Zero-Shot Learning with Language Models","created":"2022-10-26","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":"2403.14341","title":"Beyond Surface Similarity: Detecting Subtle Semantic Shifts in Financial Narratives","created":"2024-03-21","cited_by_count":13,"area":null},{"id":"2405.10040","title":"SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation","created":"2024-05-16","cited_by_count":13,"area":null},{"id":"2410.17170","title":"Self-calibration for Language Model Quantization and Pruning","created":"2024-10-22","cited_by_count":13,"area":null},{"id":"2205.12604","title":"Leveraging QA Datasets to Improve Generative Data Augmentation","created":"2022-05-25","cited_by_count":12,"area":null},{"id":"2301.01764","title":"UniHD at TSAR-2022 Shared Task: Is Compute All We Need for Lexical Simplification?","created":"2023-01-04","cited_by_count":12,"area":null},{"id":"2302.09715","title":"What happens before and after: Multi-Event Commonsense in Event Coreference Resolution","created":"2023-02-20","cited_by_count":12,"area":null},{"id":"2303.13360","title":"Towards the Scalable Evaluation of Cooperativeness in Language Models","created":"2023-03-16","cited_by_count":12,"area":null},{"id":"2305.12641","title":"A Comprehensive Survey of Sentence Representations: From the BERT Epoch to the ChatGPT Era and Beyond","created":"2023-05-22","cited_by_count":12,"area":null},{"id":"2305.13917","title":"Generating Data for Symbolic Language with Large Language Models","created":"2023-05-23","cited_by_count":12,"area":null},{"id":"2203.07613","title":"CARETS: A Consistency And Robustness Evaluative Test Suite for VQA","created":"2022-03-15","cited_by_count":11,"area":null},{"id":"2307.02006","title":"PULSAR at MEDIQA-Sum 2023: Large Language Models Augmented by Synthetic Dialogue Convert Patient Dialogues to Medical Records","created":"2023-07-05","cited_by_count":11,"area":null},{"id":"2309.05203","title":"From Artificially Real to Real: Leveraging Pseudo Data from Large Language Models for Low-Resource Molecule Discovery","created":"2023-09-11","cited_by_count":11,"area":null},{"id":"2303.16028","title":"Synthetically generated text for supervised text analysis","created":"2023-03-28","cited_by_count":10,"area":null},{"id":"2309.12426","title":"Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challenges","created":"2023-09-21","cited_by_count":9,"area":null},{"id":"2402.11532","title":"Chain-of-Instructions: Compositional Instruction Tuning on Large Language Models","created":"2024-02-18","cited_by_count":9,"area":null},{"id":"2305.18623","title":"Alfred: A System for Prompted Weak Supervision","created":"2023-05-29","cited_by_count":8,"area":null},{"id":"2308.04114","title":"Collective Human Opinions in Semantic Textual Similarity","created":"2023-08-08","cited_by_count":8,"area":null},{"id":"2205.08675","title":"Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation","created":"2022-05-18","cited_by_count":7,"area":null},{"id":"2210.16838","title":"Counterfactual Data Augmentation via Perspective Transition for Open-Domain Dialogues","created":"2022-10-30","cited_by_count":7,"area":null},{"id":"2309.09582","title":"Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs","created":"2023-09-18","cited_by_count":7,"area":null},{"id":"2310.04003","title":"The Role of Federated Learning in a Wireless World with Foundation Models","created":"2023-10-06","cited_by_count":7,"area":null},{"id":"2403.00462","title":"LUCID: LLM-Generated Utterances for Complex and Interesting Dialogues","created":"2024-03-01","cited_by_count":7,"area":null},{"id":"2403.02586","title":"Improving Event Definition Following For Zero-Shot Event Detection","created":"2024-03-05","cited_by_count":7,"area":null},{"id":"2208.08010","title":"ShortcutLens: A Visual Analytics Approach for Exploring Shortcuts in Natural Language Understanding Dataset","created":"2022-08-17","cited_by_count":6,"area":null},{"id":"2305.15090","title":"STAR: Boosting Low-Resource Information Extraction by Structure-to-Text Data Generation with Large Language Models","created":"2023-05-24","cited_by_count":6,"area":null},{"id":"2306.02754","title":"PULSAR: Pre-training with Extracted Healthcare Terms for Summarising Patients' Problems and Data Augmentation with Black-box Large Language Models","created":"2023-06-05","cited_by_count":6,"area":null},{"id":"2308.04386","title":"Learning Evaluation Models from Large Language Models for Sequence Generation","created":"2023-08-08","cited_by_count":6,"area":null},{"id":"2404.05825","title":"LLM-Augmented Retrieval: Enhancing Retrieval Models Through Language Models and Doc-Level Embedding","created":"2024-04-08","cited_by_count":6,"area":null},{"id":"2305.16000","title":"Do You Hear The People Sing? Key Point Analysis via Iterative Clustering and Abstractive Summarisation","created":"2023-05-25","cited_by_count":5,"area":null},{"id":"2306.04101","title":"Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation","created":"2023-06-07","cited_by_count":5,"area":null},{"id":"2312.11075","title":"Split and Rephrase with Large Language Models","created":"2023-12-18","cited_by_count":5,"area":null},{"id":"2401.17703","title":"WSC+: Enhancing The Winograd Schema Challenge Using Tree-of-Experts","created":"2024-01-31","cited_by_count":5,"area":null},{"id":"2402.01821","title":"Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks","created":"2024-02-02","cited_by_count":5,"area":null},{"id":"2506.03484","title":"Explainable AI: XAI-Guided Context-Aware Data Augmentation","created":"2025-06-04","cited_by_count":5,"area":null},{"id":"2108.12582","title":"Distilling the Knowledge of Large-scale Generative Models into Retrieval Models for Efficient Open-domain Conversation","created":"2021-08-28","cited_by_count":4,"area":null},{"id":"2212.01146","title":"SumREN: Summarizing Reported Speech about Events in News","created":"2022-12-02","cited_by_count":4,"area":null},{"id":"2406.15695","title":"SS-GEN: A Social Story Generation Framework with Large Language Models","created":"2024-06-22","cited_by_count":4,"area":null},{"id":"2408.09386","title":"Game Development as Human-LLM Interaction","created":"2024-08-18","cited_by_count":4,"area":null},{"id":"2409.01787","title":"LLM-GAN: Construct Generative Adversarial Network Through Large Language Models For Explainable Fake News Detection","created":"2024-09-03","cited_by_count":4,"area":null},{"id":"2410.16505","title":"Do Audio-Language Models Understand Linguistic Variations?","created":"2024-10-21","cited_by_count":4,"area":null},{"id":"2411.13485","title":"Utilizing Large Language Models to Synthesize Product Desirability Datasets","created":"2024-11-20","cited_by_count":4,"area":null}],"next_cursor":"100"}