{"total":99,"rows":[{"id":"2202.03629","title":"Survey of Hallucination in Natural Language Generation","created":"2022-02-08","cited_by_count":2075,"area":null},{"id":"2202.06935","title":"Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text","created":"2022-02-14","cited_by_count":155,"area":null},{"id":"2201.05337","title":"A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Models","created":"2022-01-14","cited_by_count":129,"area":null},{"id":"2104.07606","title":"Planning with Learned Entity Prompts for Abstractive Summarization","created":"2021-04-15","cited_by_count":75,"area":null},{"id":"2107.06963","title":"Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features","created":"2021-07-14","cited_by_count":74,"area":null},{"id":"2108.13740","title":"Plan-then-Generate: Controlled Data-to-Text Generation via Planning","created":"2021-08-31","cited_by_count":52,"area":null},{"id":"2109.02707","title":"Text-to-Table: A New Way of Information Extraction","created":"2021-09-06","cited_by_count":47,"area":null},{"id":"2207.00397","title":"Conditional Generation with a Question-Answering Blueprint","created":"2022-07-01","cited_by_count":44,"area":null},{"id":"2102.02810","title":"Controlling Hallucinations at Word Level in Data-to-Text Generation","created":"2021-02-04","cited_by_count":41,"area":null},{"id":"2109.02903","title":"IndicBART: A Pre-trained Model for Indic Natural Language Generation","created":"2021-09-07","cited_by_count":39,"area":null},{"id":"2102.02723","title":"Data-to-text Generation with Macro Planning","created":"2021-02-04","cited_by_count":34,"area":null},{"id":"2109.04953","title":"Does Pretraining for Summarization Require Knowledge Transfer?","created":"2021-09-10","cited_by_count":30,"area":null},{"id":"2404.03381","title":"Learning to Plan and Generate Text with Citations","created":"2024-04-04","cited_by_count":28,"area":null},{"id":"2102.08585","title":"Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View","created":"2021-02-17","cited_by_count":24,"area":null},{"id":"2106.10158","title":"Learning to Complete Code with Sketches","created":"2021-06-18","cited_by_count":23,"area":null},{"id":"2101.11429","title":"TSQA: Tabular Scenario Based Question Answering","created":"2021-01-14","cited_by_count":21,"area":null},{"id":"2105.14778","title":"Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation","created":"2021-05-31","cited_by_count":21,"area":null},{"id":"2108.12516","title":"Few-Shot Table-to-Text Generation with Prototype Memory","created":"2021-08-27","cited_by_count":21,"area":null},{"id":"2203.16279","title":"Neural Pipeline for Zero-Shot Data-to-Text Generation","created":"2022-03-30","cited_by_count":19,"area":null},{"id":"2105.13135","title":"Self-Supervised Multimodal Opinion Summarization","created":"2021-05-27","cited_by_count":18,"area":null},{"id":"2203.11370","title":"Language modeling via stochastic processes","created":"2022-03-21","cited_by_count":18,"area":null},{"id":"2202.13756","title":"Data-to-text Generation with Variational Sequential Planning","created":"2022-02-28","cited_by_count":17,"area":null},{"id":"2205.12697","title":"PLOG: Table-to-Logic Pretraining for Logical Table-to-Text Generation","created":"2022-05-25","cited_by_count":16,"area":null},{"id":"2401.10186","title":"Beyond Traditional Benchmarks: Analyzing Behaviors of Open LLMs on Data-to-Text Generation","created":"2024-01-18","cited_by_count":16,"area":null},{"id":"2210.04325","title":"ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models","created":"2022-10-09","cited_by_count":14,"area":null},{"id":"2305.05290","title":"Dialogue Planning via Brownian Bridge Stochastic Process for Goal-directed Proactive Dialogue","created":"2023-05-09","cited_by_count":14,"area":null},{"id":"2412.15249","title":"LitLLMs, LLMs for Literature Review: Are we there yet?","created":"2024-12-15","cited_by_count":14,"area":null},{"id":"2108.06897","title":"AutoChart: A Dataset for Chart-to-Text Generation Task","created":"2021-08-16","cited_by_count":13,"area":null},{"id":"2308.04813","title":"CLEVA: Chinese Language Models EVAluation Platform","created":"2023-08-09","cited_by_count":13,"area":null},{"id":"2305.19204","title":"SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pages","created":"2023-05-30","cited_by_count":12,"area":null},{"id":"2310.15079","title":"Affective and Dynamic Beam Search for Story Generation","created":"2023-10-23","cited_by_count":12,"area":null},{"id":"2105.08021","title":"Stage-wise Fine-tuning for Graph-to-Text Generation","created":"2021-05-17","cited_by_count":11,"area":null},{"id":"2411.02540","title":"GraphXAIN: Narratives to Explain Graph Neural Networks","created":"2024-11-04","cited_by_count":11,"area":null},{"id":"2103.07170","title":"Constrained Text Generation with Global Guidance -- Case Study on CommonGen","created":"2021-03-12","cited_by_count":10,"area":null},{"id":"2207.12571","title":"Innovations in Neural Data-to-text Generation: A Survey","created":"2022-07-25","cited_by_count":10,"area":null},{"id":"2108.05644","title":"Generation Challenges: Results of the Accuracy Evaluation Shared Task","created":"2021-08-12","cited_by_count":9,"area":null},{"id":"2109.01518","title":"Biomedical Data-to-Text Generation via Fine-Tuning Transformers","created":"2021-09-03","cited_by_count":9,"area":null},{"id":"2305.00034","title":"Text-Blueprint: An Interactive Platform for Plan-based Conditional Generation","created":"2023-04-28","cited_by_count":9,"area":null},{"id":"2303.14956","title":"Unified Text Structuralization with Instruction-tuned Language Models","created":"2023-03-27","cited_by_count":8,"area":null},{"id":"2305.03276","title":"Expository Text Generation: Imitate, Retrieve, Paraphrase","created":"2023-05-05","cited_by_count":8,"area":null},{"id":"2106.05580","title":"AGGGEN: Ordering and Aggregating while Generating","created":"2021-06-10","cited_by_count":7,"area":null},{"id":"2204.05879","title":"Generating Full Length Wikipedia Biographies: The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographies","created":"2022-04-12","cited_by_count":7,"area":null},{"id":"2305.14205","title":"$\\mu$PLAN: Summarizing using a Content Plan as Cross-Lingual Bridge","created":"2023-05-23","cited_by_count":7,"area":null},{"id":"2103.09656","title":"Set-to-Sequence Methods in Machine Learning: a Review","created":"2021-03-17","cited_by_count":6,"area":null},{"id":"2302.09820","title":"Improving User Controlled Table-To-Text Generation Robustness","created":"2023-02-20","cited_by_count":6,"area":null},{"id":"2403.06063","title":"Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive Dialogue","created":"2024-03-10","cited_by_count":6,"area":null},{"id":"2409.19747","title":"Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directions","created":"2024-09-29","cited_by_count":6,"area":null},{"id":"2110.05633","title":"TCube: Domain-Agnostic Neural Time-series Narration","created":"2021-10-11","cited_by_count":5,"area":null},{"id":"2111.07935","title":"Incorporating Question Answering-Based Signals into Abstractive Summarization via Salient Span Selection","created":"2021-11-15","cited_by_count":5,"area":null},{"id":"2310.18794","title":"Sequence-Level Certainty Reduces Hallucination In Knowledge-Grounded Dialogue Generation","created":"2023-10-28","cited_by_count":5,"area":null},{"id":"2311.09467","title":"Think While You Write: Hypothesis Verification Promotes Faithful Knowledge-to-Text Generation","created":"2023-11-16","cited_by_count":5,"area":null},{"id":"2501.03857","title":"Progressive Document-level Text Simplification via Large Language Models","created":"2025-01-07","cited_by_count":5,"area":null},{"id":"2101.08248","title":"Data-to-text Generation by Splicing Together Nearest Neighbors","created":"2021-01-20","cited_by_count":4,"area":null},{"id":"2104.07228","title":"Sentence-Permuted Paragraph Generation","created":"2021-04-15","cited_by_count":4,"area":null},{"id":"2205.11055","title":"TempLM: Distilling Language Models into Template-Based Generators","created":"2022-05-23","cited_by_count":4,"area":null},{"id":"2301.02071","title":"Towards Table-to-Text Generation with Pretrained Language Model: A Table Structure Understanding and Text Deliberating Approach","created":"2023-01-05","cited_by_count":4,"area":null},{"id":"2308.03117","title":"PromptSum: Parameter-Efficient Controllable Abstractive Summarization","created":"2023-08-06","cited_by_count":4,"area":null},{"id":"2402.08496","title":"A Systematic Review of Data-to-Text NLG","created":"2024-02-13","cited_by_count":4,"area":null},{"id":"2504.19339","title":"Explanatory Summarization with Discourse-Driven Planning","created":"2025-04-27","cited_by_count":4,"area":null},{"id":"2112.10360","title":"May the Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation","created":"2021-12-20","cited_by_count":3,"area":null},{"id":"2204.04977","title":"Regularization-based Pruning of Irrelevant Weights in Deep Neural Architectures","created":"2022-04-11","cited_by_count":3,"area":null},{"id":"2212.10935","title":"Commentary Generation from Data Records of Multiplayer Strategy Esports Game","created":"2022-12-21","cited_by_count":3,"area":null},{"id":"2309.12551","title":"Is it Possible to Modify Text to a Target Readability Level? An Initial Investigation Using Zero-Shot Large Language Models","created":"2023-09-22","cited_by_count":3,"area":null},{"id":"2403.07567","title":"Triples-to-isiXhosa (T2X): Addressing the Challenges of Low-Resource Agglutinative Data-to-Text Generation","created":"2024-03-12","cited_by_count":3,"area":null},{"id":"2404.02466","title":"Prompting for Numerical Sequences: A Case Study on Market Comment Generation","created":"2024-04-03","cited_by_count":3,"area":null},{"id":"2404.04103","title":"Improving Factual Accuracy of Neural Table-to-Text Output by Addressing Input Problems in ToTTo","created":"2024-04-05","cited_by_count":3,"area":null},{"id":"2407.11449","title":"Controllable Contextualized Image Captioning: Directing the Visual Narrative through User-Defined Highlights","created":"2024-07-16","cited_by_count":3,"area":null},{"id":"2409.07088","title":"Ontology-Free General-Domain Knowledge Graph-to-Text Generation Dataset Synthesis using Large Language Model","created":"2024-09-11","cited_by_count":3,"area":null},{"id":"2101.08675","title":"Adversarial Machine Learning in Text Analysis and Generation","created":"2021-01-14","cited_by_count":2,"area":null},{"id":"2302.05138","title":"Plan-then-Seam: Towards Efficient Table-to-Text Generation","created":"2023-02-10","cited_by_count":2,"area":null},{"id":"2306.15933","title":"You Can Generate It Again: Data-to-Text Generation with Verification and Correction Prompting","created":"2023-06-28","cited_by_count":2,"area":null},{"id":"2308.05317","title":"Few-Shot Data-to-Text Generation via Unified Representation and Multi-Source Learning","created":"2023-08-10","cited_by_count":2,"area":null},{"id":"2310.17279","title":"Automatic Logical Forms improve fidelity in Table-to-Text generation","created":"2023-10-26","cited_by_count":2,"area":null},{"id":"2508.15910","title":"Evaluating Structured Decoding for Text-to-Table Generation: Evidence from Three Datasets","created":"2025-08-21","cited_by_count":2,"area":null},{"id":"2108.08111","title":"Table Caption Generation in Scholarly Documents Leveraging Pre-trained Language Models","created":"2021-08-18","cited_by_count":1,"area":null},{"id":"2204.04686","title":"DISK: Domain-constrained Instance Sketch for Math Word Problem Generation","created":"2022-04-10","cited_by_count":1,"area":null},{"id":"2205.12368","title":"Medical Scientific Table-to-Text Generation with Human-in-the-Loop under the Data Sparsity Constraint","created":"2022-05-24","cited_by_count":1,"area":null},{"id":"2207.05194","title":"Towards Neural Numeric-To-Text Generation From Temporal Personal Health Data","created":"2022-07-11","cited_by_count":1,"area":null},{"id":"2208.05757","title":"A Comprehensive Survey of Natural Language Generation Advances from the Perspective of Digital Deception","created":"2022-08-11","cited_by_count":1,"area":null},{"id":"2302.11269","title":"Learning from Multiple Sources for Data-to-Text and Text-to-Data","created":"2023-02-22","cited_by_count":1,"area":null},{"id":"2307.01548","title":"Knowledge Graph for NLG in the context of conversational agents","created":"2023-07-04","cited_by_count":1,"area":null},{"id":"2308.15898","title":"An xAI Approach for Data-to-Text Processing with ASP","created":"2023-08-30","cited_by_count":1,"area":null},{"id":"2406.10560","title":"Facts-and-Feelings: Capturing both Objectivity and Subjectivity in Table-to-Text Generation","created":"2024-06-15","cited_by_count":1,"area":null},{"id":"2407.14088","title":"Impact of Model Size on Fine-tuned LLM Performance in Data-to-Text Generation: A State-of-the-Art Investigation","created":"2024-07-19","cited_by_count":1,"area":null},{"id":"2509.17037","title":"KAHAN: Knowledge-Augmented Hierarchical Analysis and Narration for Financial Data Narration","created":"2025-09-21","cited_by_count":1,"area":null},{"id":"2602.07499","title":"Let's Simplify Step by Step: Guiding LLM Towards Multilingual Unsupervised Proficiency-Controlled Sentence Simplification","created":"2026-02-07","cited_by_count":1,"area":null},{"id":"2108.07998","title":"GGP: A Graph-based Grouping Planner for Explicit Control of Long Text Generation","created":"2021-08-18","cited_by_count":0,"area":null},{"id":"2112.04344","title":"Does Structure Matter? Leveraging Data-to-Text Generation for Answering Complex Information Needs","created":"2021-12-08","cited_by_count":0,"area":null},{"id":"2203.12106","title":"An Empirical Study on Learning and Improving the Search Objective for Unsupervised Paraphrasing","created":"2022-03-23","cited_by_count":0,"area":null},{"id":"2208.04558","title":"High Recall Data-to-text Generation with Progressive Edit","created":"2022-08-09","cited_by_count":0,"area":null},{"id":"2302.06470","title":"POSGen: Personalized Opening Sentence Generation for Online Insurance Sales","created":"2023-02-10","cited_by_count":0,"area":null},{"id":"2304.08243","title":"Stochastic Code Generation","created":"2023-04-14","cited_by_count":0,"area":null},{"id":"2501.14497","title":"Evaluating and Improving Graph to Text Generation with Large Language Models","created":"2025-01-24","cited_by_count":0,"area":null},{"id":"2503.23204","title":"The Challenge of Achieving Attributability in Multilingual Table-to-Text Generation with Question-Answer Blueprints","created":"2025-03-29","cited_by_count":0,"area":null},{"id":"2510.21034","title":"Input Matters: Evaluating Input Structure's Impact on LLM Summaries of Sports Play-by-Play","created":"2025-10-23","cited_by_count":0,"area":null},{"id":"2604.26501","title":"Tree-of-Text: A Tree-based Prompting Framework for Table-to-Text Generation in the Sports Domain","created":"2026-04-29","cited_by_count":0,"area":null},{"id":"2608.23391","title":"Cross-Domain, Multi-Task Data-to-Text Generation without In-Domain Training Data","created":"2026-08-24","cited_by_count":0,"area":null},{"id":"2608.25336","title":"Provenance Before Prose: Claim-Locked Reporting for Statistical Text Generation","created":"2026-08-26","cited_by_count":0,"area":null},{"id":"2609.00818","title":"AnalysisBank: An Expert Analysis Pattern Library for Financial Report Generation","created":"2026-09-01","cited_by_count":0,"area":null}],"next_cursor":null}