Centrala begrepp
Large Language Models (LLMs) struggle to generate complex structured tabular data, despite their advanced text generation capabilities. This study introduces a comprehensive benchmark, STRUC-BENCH, to assess LLMs' performance on this task and proposes a structure-aware fine-tuning method to improve their abilities.
Sammanfattning
The study examines the challenges faced by Large Language Models (LLMs) in generating complex structured tabular data, which is an essential skill for practical applications like coding copilots and automated report generation.
The key highlights are:
Lack of systematic analysis and comprehensive benchmarks to evaluate LLMs' ability to output complex structured tabular data. Previous efforts have focused on simple Information Extraction (IE) tasks rather than structured data generation.
Lack of evaluation metrics that consider both the content and format of the generated tables. Existing benchmarks rely on rudimentary metrics like word overlap, which may be insufficient for evaluating structured output.
Lack of methods to enhance the performance of current LLMs to better follow natural language inputs and generate tabular outputs with the correct format.
The study introduces STRUC-BENCH, a benchmark specifically constructed for generating structured tabular data, covering text tables, HTML, and LaTeX formats. It also proposes two innovative metrics, P-Score and H-Score, to more accurately gauge LLM performance on this task.
Furthermore, the study presents a structure-aware fine-tuning method, FORMATCOT, which utilizes GPT-3.5 to generate format instructions and then fine-tunes the LLaMA-7B model to follow these formats. The results demonstrate that with FORMATCOT, smaller models can outperform larger models in this specific task.
The study also provides an in-depth error analysis and creates an ability map across six dimensions - coverage, formatting, reasoning, comprehension, pragmatics, and hallucination - to highlight areas for future enhancements and suggest forthcoming research trajectories.
Statistik
The Grizzlies shot 50 percent from the field.
The Grizzlies outscored the Suns 30-19 in the third quarter and 26-20 in the final period.
The Grizzlies out-rebounded Phoenix 37-35 and outscored the Suns in the paint 46-32.
The Grizzlies registered 25 assists compared to only 13 for the Suns.
Courtney Lee scored 22 points (9-14 FG, 4-5 3Pt).
Mike Conley led all scorers with 24 points (9-14 FG, 3-4 3Pt) and 11 assists.
Marc Gasol added 18 points, six assists, and five rebounds.
Eric Bledsoe scored 23 points (9-12 FG) with five rebounds and four assists.
Goran Dragic scored just six points in 26 minutes.
Isaiah Thomas had 15 points and two assists off the bench.
Markieff Morris added 20 points and five rebounds.
Citat
"The Grizzlies (50) used a strong second half to outlast the Suns (3 - 2) 102 - 91 in Phoenix on Wednesday night."
"Memphis found itself behind six at halftime but outscored Phoenix 30 - 19 in the third quarter and 26 - 20 in the final period."
"The Grizzlies shot 50 percent from the field, led by strong performances from Courtney Lee and Mike Conley."