Papers Table-to-Text Generation
“Table-to-Text Generation” 태그가 달린 논문 71편 · 필터 해제
Tree-of-Text: A Tree-based Prompting Framework for Table-to-Text Generation in the Sports Domain
Generating sports game reports from structured tables is a complex table-to-text task that demands both precise data interpretation and fluent narrative generation. Traditional model-based approaches require large, annot…
Table-to-Text GenerationTowards Improving Interpretability of Language Model Generation through a Structured Knowledge Discovery Approach
Knowledge-enhanced text generation aims to enhance the quality of generated text by utilizing internal or external knowledge sources. While language models have demonstrated impressive capabilities in generating coherent…
Table-to-Text GenerationRepresentation LearningResponse GenerationFreshTab: Sourcing Fresh Data for Table-to-Text Generation Evaluation
Table-to-text generation (insight generation from tables) is a challenging task that requires precision in analyzing the data. In addition, the evaluation of existing benchmarks is affected by contamination of Large Lang…
Table-to-Text GenerationThe Challenge of Achieving Attributability in Multilingual Table-to-Text Generation with Question-Answer Blueprints
Multilingual Natural Language Generation (NLG) is challenging due to the lack of training data for low-resource languages. However, some low-resource languages have up to tens of millions of speakers globally, making it …
Table-to-Text GenerationText GenerationDETQUS: Decomposition-Enhanced Transformers for QUery-focused Summarization
Query-focused tabular summarization is an emerging task in table-to-text generation that synthesizes a summary response from tabular data based on user queries. Traditional transformer-based approaches face challenges du…
DecoderLanguage ModelingLanguage ModellingLarge Language Model+3Towards More Effective Table-to-Text Generation: Assessing In-Context Learning and Self-Evaluation with Open-Source Models
Table processing, a key task in natural language processing, has significantly benefited from recent advancements in language models (LMs). However, the capabilities of LMs in table-to-text generation, which transforms s…
In-Context LearningLanguage ModelingLanguage ModellingLarge Language Model+2Table-to-Text Generation with Pretrained Diffusion Models
Diffusion models have demonstrated significant potential in achieving state-of-the-art performance across various text generation tasks. In this systematic study, we investigate their application to the table-to-text pro…
DiversityTable-to-Text GenerationText GenerationFacts-and-Feelings: Capturing both Objectivity and Subjectivity in Table-to-Text Generation
Table-to-text generation, a long-standing challenge in natural language generation, has remained unexplored through the lens of subjectivity. Subjectivity here encompasses the comprehension of information derived from th…
Table-to-Text GenerationText GenerationExploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data
Augmenting Large Language Models (LLMs) for Question Answering (QA) with domain specific data has attracted wide attention. However, domain data often exists in a hybrid format, including text and semi-structured tables,…
Question AnsweringRAGTable-to-Text GenerationText GenerationTowards Controlled Table-to-Text Generation with Scientific Reasoning
The sheer volume of scientific experimental results and complex technical statements, often presented in tabular formats, presents a formidable barrier to individuals acquiring preferred information. The realms of scient…
Table-to-Text GenerationText GenerationPixT3: Pixel-based Table-To-Text Generation
Table-to-text generation involves generating appropriate textual descriptions given structured tabular data. It has attracted increasing attention in recent years thanks to the popularity of neural network models and the…
Data-to-Text GenerationSelf-Supervised LearningTable-to-Text GenerationText GenerationHeLM: Highlighted Evidence augmented Language Model for Enhanced Table-to-Text Generation
Large models have demonstrated significant progress across various domains, particularly in tasks related to text generation. In the domain of Table to Text, many Large Language Model (LLM)-based methods currently resort…
Language ModelingLanguage ModellingLarge Language Modelparameter-efficient fine-tuning+2Automatic Logical Forms improve fidelity in Table-to-Text generation
Table-to-text systems generate natural language statements from structured data like tables. While end-to-end techniques suffer from low factual correctness (fidelity), a previous study reported gains when using manual l…
Table-to-Text GenerationText GenerationFactSpotter: Evaluating the Factual Faithfulness of Graph-to-Text Generation
Graph-to-text (G2T) generation takes a graph as input and aims to generate a fluent and faith- ful textual representation of the information in the graph. The task has many applications, such as dialogue generation and q…
Data-to-Text GenerationDialogue GenerationKG-to-Text GenerationQuestion Generation+2Effective Distillation of Table-based Reasoning Ability from LLMs
Large Language Models (LLMs) have demonstrated remarkable performance across a wide range of natural language processing tasks. However, their enormous parameter size and extremely high requirements for compute power pos…
Table-to-Text GenerationText GenerationTackling Hallucinations in Neural Chart Summarization
Hallucinations in text generation occur when the system produces text that is not grounded in the input. In this work, we tackle the problem of hallucinations in neural chart summarization. Our analysis shows that the ta…
Data-to-Text GenerationTable-to-Text GenerationText GenerationInvestigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios
Tabular data is prevalent across various industries, necessitating significant time and effort for users to understand and manipulate for their information-seeking purposes. The advancements in large language models (LLM…
Table-to-Text GenerationText GenerationQTSumm: Query-Focused Summarization over Tabular Data
People primarily consult tables to conduct data analysis or answer specific questions. Text generation systems that can provide accurate table summaries tailored to users' information needs can facilitate more efficient …
Query-focused SummarizationTable-to-Text GenerationText GenerationReTAG: Reasoning Aware Table to Analytic Text Generation
The task of table summarization involves generating text that both succinctly and accurately represents the table or a specific set of highlighted cells within a table. While significant progress has been made in table t…
Data-to-Text GenerationDescriptiveQuantizationTable-to-Text Generation+1Towards Zero-Shot Personalized Table-to-Text Generation with Contrastive Persona Distillation
Existing neural methods have shown great potentials towards generating informative text from structured tabular data as well as maintaining high content fidelity. However, few of them shed light on generating personalize…
Table-to-Text GenerationText Generation