{"total":104,"rows":[{"id":"2212.10450","title":"Is GPT-3 a Good Data Annotator?","created":"2022-12-20","cited_by_count":208,"area":null},{"id":"2312.17617","title":"Large Language Models for Generative Information Extraction: A Survey","created":"2023-12-29","cited_by_count":185,"area":null},{"id":"2304.08085","title":"InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction","created":"2023-04-17","cited_by_count":170,"area":null},{"id":"2310.03668","title":"GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction","created":"2023-10-05","cited_by_count":119,"area":null},{"id":"2306.04618","title":"Revisiting Out-of-distribution Robustness in NLP: Benchmark, Analysis, and LLMs Evaluations","created":"2023-06-07","cited_by_count":97,"area":null},{"id":"2311.08526","title":"GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer","created":"2023-11-14","cited_by_count":88,"area":null},{"id":"2103.11332","title":"AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive Summarization","created":"2021-03-21","cited_by_count":51,"area":null},{"id":"2502.10708","title":"Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey","created":"2025-02-15","cited_by_count":51,"area":null},{"id":"2301.03282","title":"Universal Information Extraction as Unified Semantic Matching","created":"2023-01-09","cited_by_count":48,"area":null},{"id":"2305.15444","title":"PromptNER: Prompting For Named Entity Recognition","created":"2023-05-24","cited_by_count":35,"area":null},{"id":"2209.06664","title":"SPACE-3: Unified Dialog Model Pre-training for Task-Oriented Dialog Understanding and Generation","created":"2022-09-14","cited_by_count":34,"area":null},{"id":"2403.07969","title":"KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction","created":"2024-03-12","cited_by_count":34,"area":null},{"id":"2403.04190","title":"Generative AI for Synthetic Data Generation: Methods, Challenges and the Future","created":"2024-03-07","cited_by_count":33,"area":"synth"},{"id":"2409.11968","title":"Efficacy of Synthetic Data as a Benchmark","created":"2024-09-18","cited_by_count":30,"area":"synth"},{"id":"2105.03953","title":"Continual Mixed-Language Pre-Training for Extremely Low-Resource Neural Machine Translation","created":"2021-05-09","cited_by_count":29,"area":null},{"id":"2209.06638","title":"SPACE-2: Tree-Structured Semi-Supervised Contrastive Pre-training for Task-Oriented Dialog Understanding","created":"2022-09-14","cited_by_count":28,"area":null},{"id":"2210.09345","title":"CrossRE: A Cross-Domain Dataset for Relation Extraction","created":"2022-10-17","cited_by_count":21,"area":null},{"id":"2210.12623","title":"Model and Data Transfer for Cross-Lingual Sequence Labelling in Zero-Resource Settings","created":"2022-10-23","cited_by_count":21,"area":null},{"id":"2312.15548","title":"YAYI-UIE: A Chat-Enhanced Instruction Tuning Framework for Universal Information Extraction","created":"2023-12-24","cited_by_count":19,"area":null},{"id":"2308.10529","title":"SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding","created":"2023-08-21","cited_by_count":18,"area":null},{"id":"2204.13516","title":"What do You Mean by Relation Extraction? A Survey on Datasets and Study on Scientific Relation Classification","created":"2022-04-28","cited_by_count":17,"area":null},{"id":"2206.03352","title":"Searching for Optimal Subword Tokenization in Cross-domain NER","created":"2022-06-07","cited_by_count":17,"area":null},{"id":"2105.12969","title":"Improve Query Focused Abstractive Summarization by Incorporating Answer Relevance","created":"2021-05-27","cited_by_count":15,"area":null},{"id":"2109.01758","title":"Data Augmentation for Cross-Domain Named Entity Recognition","created":"2021-09-04","cited_by_count":14,"area":null},{"id":"2212.10548","title":"T-Projection: High Quality Annotation Projection for Sequence Labeling Tasks","created":"2022-12-20","cited_by_count":14,"area":null},{"id":"2402.16602","title":"Rethinking Negative Instances for Generative Named Entity Recognition","created":"2024-02-26","cited_by_count":13,"area":"lr"},{"id":"2311.05419","title":"Mirror: A Universal Framework for Various Information Extraction Tasks","created":"2023-11-09","cited_by_count":12,"area":null},{"id":"2101.03841","title":"Model Generalization on COVID-19 Fake News Detection","created":"2021-01-11","cited_by_count":11,"area":null},{"id":"2301.10410","title":"One Model for All Domains: Collaborative Domain-Prefix Tuning for Cross-Domain NER","created":"2023-01-25","cited_by_count":11,"area":null},{"id":"2308.14533","title":"A Multi-Task Semantic Decomposition Framework with Task-specific Pre-training for Few-Shot NER","created":"2023-08-28","cited_by_count":9,"area":null},{"id":"2507.18546","title":"GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface","created":"2025-07-24","cited_by_count":9,"area":null},{"id":"2210.04676","title":"Learning \"O\" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER","created":"2022-10-10","cited_by_count":8,"area":null},{"id":"2403.12749","title":"Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal Data","created":"2024-03-19","cited_by_count":8,"area":null},{"id":"2208.11464","title":"FactMix: Using a Few Labeled In-domain Examples to Generalize to Cross-domain Named Entity Recognition","created":"2022-08-24","cited_by_count":7,"area":null},{"id":"2210.11255","title":"Evidence > Intuition: Transferability Estimation for Encoder Selection","created":"2022-10-20","cited_by_count":7,"area":null},{"id":"2304.14770","title":"RexUIE: A Recursive Method with Explicit Schema Instructor for Universal Information Extraction","created":"2023-04-28","cited_by_count":7,"area":null},{"id":"2309.10706","title":"OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch","created":"2023-09-19","cited_by_count":7,"area":null},{"id":"2210.10343","title":"Entity-to-Text based Data Augmentation for various Named Entity Recognition Tasks","created":"2022-10-19","cited_by_count":6,"area":null},{"id":"2310.02953","title":"JsonTuning: Towards Generalizable, Robust, and Controllable Instruction Tuning","created":"2023-10-04","cited_by_count":6,"area":null},{"id":"2402.04838","title":"PaDeLLM-NER: Parallel Decoding in Large Language Models for Named Entity Recognition","created":"2024-02-07","cited_by_count":6,"area":"inference"},{"id":"2509.09082","title":"MR-UIE: Multi-Perspective Reasoning with Reinforcement Learning for Universal Information Extraction","created":"2025-09-11","cited_by_count":6,"area":"lr"},{"id":"2108.10808","title":"Greenformers: Improving Computation and Memory Efficiency in Transformer Models via Low-Rank Approximation","created":"2021-08-24","cited_by_count":5,"area":null},{"id":"2305.10985","title":"Multi-CrossRE A Multi-Lingual Multi-Domain Dataset for Relation Extraction","created":"2023-05-18","cited_by_count":5,"area":null},{"id":"2402.14710","title":"IEPile: Unearthing Large-Scale Schema-Based Information Extraction Corpus","created":"2024-02-22","cited_by_count":5,"area":null},{"id":"2406.11192","title":"Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition","created":"2024-06-17","cited_by_count":5,"area":null},{"id":"2407.01272","title":"Show Less, Instruct More: Enriching Prompts with Definitions and Guidelines for Zero-Shot NER","created":"2024-07-01","cited_by_count":5,"area":null},{"id":"2408.00981","title":"Cross-domain Named Entity Recognition via Graph Matching","created":"2024-08-02","cited_by_count":5,"area":null},{"id":"2409.11022","title":"DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition","created":"2024-09-17","cited_by_count":5,"area":null},{"id":"2411.00451","title":"Improving Few-Shot Cross-Domain Named Entity Recognition by Instruction Tuning a Word-Embedding based Retrieval Augmented Large Language Model","created":"2024-11-01","cited_by_count":5,"area":"rag"},{"id":"2506.06579","title":"Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques","created":"2025-06-06","cited_by_count":5,"area":null},{"id":"2106.03777","title":"X2Parser: Cross-Lingual and Cross-Domain Framework for Task-Oriented Compositional Semantic Parsing","created":"2021-06-07","cited_by_count":4,"area":null},{"id":"2402.11512","title":"From Prejudice to Parity: A New Approach to Debiasing Large Language Model Word Embeddings","created":"2024-02-18","cited_by_count":4,"area":null},{"id":"2406.10258","title":"Curating Grounded Synthetic Data with Global Perspectives for Equitable AI","created":"2024-06-10","cited_by_count":4,"area":null},{"id":"2406.17305","title":"Retrieval Augmented Instruction Tuning for Open NER with Large Language Models","created":"2024-06-25","cited_by_count":4,"area":"rag"},{"id":"2412.11851","title":"A Benchmark and Robustness Study of In-Context-Learning with Large Language Models in Music Entity Detection","created":"2024-12-16","cited_by_count":4,"area":null},{"id":"2506.00649","title":"GuideX: Guided Synthetic Data Generation for Zero-Shot Information Extraction","created":"2025-05-31","cited_by_count":4,"area":"synth"},{"id":"2409.11673","title":"RUIE: Retrieval-based Unified Information Extraction using Large Language Model","created":"2024-09-18","cited_by_count":3,"area":null},{"id":"2411.04794","title":"KnowCoder-X: Boosting Multilingual Information Extraction via Code","created":"2024-11-07","cited_by_count":3,"area":null},{"id":"2412.10121","title":"Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training Data","created":"2024-12-13","cited_by_count":3,"area":null},{"id":"2505.12236","title":"Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-training","created":"2025-05-18","cited_by_count":3,"area":null},{"id":"2506.22813","title":"Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models","created":"2025-06-28","cited_by_count":3,"area":null},{"id":"2305.11016","title":"Silver Syntax Pre-training for Cross-Domain Relation Extraction","created":"2023-05-18","cited_by_count":2,"area":null},{"id":"2305.17448","title":"Measuring Your ASTE Models in The Wild: A Diversified Multi-domain Dataset For Aspect Sentiment Triplet Extraction","created":"2023-05-27","cited_by_count":2,"area":null},{"id":"2402.13693","title":"CMNER: A Chinese Multimodal NER Dataset based on Social Media","created":"2024-02-21","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":"2508.03250","title":"RooseBERT: A New Deal For Political Language Modelling","created":"2025-08-05","cited_by_count":2,"area":null},{"id":"2605.05277","title":"GLiNER Guard: Unified Encoder Family for Production LLM Safety and Privacy","created":"2026-05-06","cited_by_count":2,"area":"safety"},{"id":"2210.07523","title":"Self-Adaptive Named Entity Recognition by Retrieving Unstructured Knowledge","created":"2022-10-14","cited_by_count":1,"area":null},{"id":"2308.10564","title":"Software Entity Recognition with Noise-Robust Learning","created":"2023-08-21","cited_by_count":1,"area":null},{"id":"2401.10189","title":"Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text Reconstruction","created":"2024-01-18","cited_by_count":1,"area":null},{"id":"2410.13118","title":"Retrieval-Enhanced Named Entity Recognition","created":"2024-10-17","cited_by_count":1,"area":null},{"id":"2410.23452","title":"Graph-Augmented Relation Extraction Model with LLMs-Generated Support Document","created":"2024-10-30","cited_by_count":1,"area":null},{"id":"2502.12614","title":"Label Drop for Multi-Aspect Relation Modeling in Universal Information Extraction","created":"2025-02-18","cited_by_count":1,"area":null},{"id":"2505.12533","title":"Relation Extraction or Pattern Matching? Unravelling the Generalisation Limits of Language Models for Biographical RE","created":"2025-05-18","cited_by_count":1,"area":null},{"id":"2108.10561","title":"Taming the Beast: Learning to Control Neural Conversational Models","created":"2021-08-24","cited_by_count":0,"area":null},{"id":"2211.08386","title":"Generative Long-form Question Answering: Relevance, Faithfulness and Succinctness","created":"2022-11-15","cited_by_count":0,"area":null},{"id":"2301.05220","title":"Adversarial Adaptation for French Named Entity Recognition","created":"2023-01-12","cited_by_count":0,"area":null},{"id":"2310.05374","title":"Improving End-to-End Speech Processing by Efficient Text Data Utilization with Latent Synthesis","created":"2023-10-09","cited_by_count":0,"area":null},{"id":"2404.13760","title":"How to Encode Domain Information in Relation Classification","created":"2024-04-21","cited_by_count":0,"area":null},{"id":"2405.05957","title":"OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning","created":"2024-05-09","cited_by_count":0,"area":null},{"id":"2409.05275","title":"RexUniNLU: Recursive Method with Explicit Schema Instructor for Universal NLU","created":"2024-09-09","cited_by_count":0,"area":null},{"id":"2505.14992","title":"Effective and Efficient Schema-aware Information Extraction Using On-Device Large Language Models","created":"2025-05-21","cited_by_count":0,"area":null},{"id":"2509.12951","title":"Black-box Model Merging for Language-Model-as-a-Service with Massive Model Repositories","created":"2025-09-16","cited_by_count":0,"area":null},{"id":"2510.07566","title":"Multi-Task Pre-Finetuning of Lightweight Transformer Encoders for Text Classification and NER","created":"2025-10-08","cited_by_count":0,"area":null},{"id":"2510.17720","title":"PANER: A Paraphrase-Augmented Framework for Low-Resource Named Entity Recognition","created":"2025-10-20","cited_by_count":0,"area":null},{"id":"2510.19410","title":"ToMMeR -- Efficient Entity Mention Detection from Large Language Models","created":"2025-10-22","cited_by_count":0,"area":null},{"id":"2511.18335","title":"OmniStruct: Universal Text-to-Structure Generation across Diverse Schemas","created":"2025-11-23","cited_by_count":0,"area":"agents"},{"id":"2512.06239","title":"LOCUS: A System and Method for Low-Cost Customization for Universal Specialization","created":"2025-12-06","cited_by_count":0,"area":null},{"id":"2512.12337","title":"SCIR: A Self-Correcting Iterative Refinement Framework for Enhanced Information Extraction Based on Schema","created":"2025-12-13","cited_by_count":0,"area":null},{"id":"2602.15189","title":"ScrapeGraphAI-100k: Dataset for Schema-Constrained LLM Generation","created":"2026-02-16","cited_by_count":0,"area":null},{"id":"2604.05158","title":"Just Pass Twice: Efficient Token Classification with LLMs for Zero-Shot NER","created":"2026-04-06","cited_by_count":0,"area":null},{"id":"2604.05624","title":"YoNER: A New Yor\\`ub\\'a Multi-domain Named Entity Recognition Dataset","created":"2026-04-07","cited_by_count":0,"area":null},{"id":"2604.15866","title":"DiZiNER: Disagreement-guided Instruction Refinement via Pilot Annotation Simulation for Zero-shot Named Entity Recognition","created":"2026-04-17","cited_by_count":0,"area":null},{"id":"2604.20447","title":"Decoding Text Spans for Efficient and Accurate Named-Entity Recognition","created":"2026-04-22","cited_by_count":0,"area":null},{"id":"2605.03706","title":"SAM-NER: Semantic Archetype Mediation for Zero-Shot Named Entity Recognition","created":"2026-05-05","cited_by_count":0,"area":null},{"id":"2606.05868","title":"YouZhi: Towards High-Concurrency Financial LLMs via Adaptive GQA-to-MLA Transition","created":"2026-06-04","cited_by_count":0,"area":"inference"},{"id":"2606.21890","title":"Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity Recognition","created":"2026-06-20","cited_by_count":0,"area":null},{"id":"2608.00013","title":"What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs","created":"2026-06-24","cited_by_count":0,"area":"mllm"},{"id":"2608.29324","title":"Pad\\=artha: Ontology-Grounded Fine-Grained NER Benchmark for Classical Sanskrit","created":"2026-08-29","cited_by_count":0,"area":null},{"id":"2608.29526","title":"Ontology-Guided Multi-Agent Extraction of Evaluation Objects from Academic Review Texts: Evidence from Chinese Library and Information Science","created":"2026-08-30","cited_by_count":0,"area":null}],"next_cursor":"100"}