Table-to-Text Generation
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Benchmarks
DART
WikiBio
E2E
WebNLG (All)
WebNLG (Seen)
WebNLG (Unseen)
RotoWire
Most implemented
Prefix-Tuning: Optimizing Continuous Prompts for Generation
What Makes Good In-Context Examples for GPT-$3$?
Table-to-text Generation by Structure-aware Seq2seq Learning
Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios
QTSumm: Query-Focused Summarization over Tabular Data
Papers
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+2