Categories: FAANG

Construction of Paired Knowledge Graph – Text Datasets Informed by Cyclic Evaluation

Datasets that pair Knowledge Graphs (KG) and text together (KG-T) can be used to train forward and reverse neural models that generate text from KG and vice versa. However models trained on datasets where KG and text pairs are not equivalent can suffer from more hallucination and poorer recall. In this paper, we verify this empirically by generating datasets with different levels of noise and find that noisier datasets do indeed lead to more hallucination. We argue that the ability of forward and reverse models trained on a dataset to cyclically regenerate source KG or text is a proxy for the…
AI Generated Robotic Content

Recent Posts

VibeVoice is crazy good (first try, no cherry-picking)

Installed VibeVoice using the wrapper this dude created. https://www.reddit.com/r/comfyui/comments/1n20407/wip2_comfyui_wrapper_for_microsofts_new_vibevoice/ Workflow is the multi-voice example one…

6 hours ago

7 Pandas Tricks for Efficient Data Merging

Data merging is the process of combining data from different sources into a unified dataset.

6 hours ago

How to Decide Between Random Forests and Gradient Boosting

When working with machine learning on structured data, two algorithms often rise to the top…

6 hours ago

Meet Boti: The AI assistant transforming how the citizens of Buenos Aires access government information with Amazon Bedrock

This post is co-written with Julieta Rappan, Macarena Blasi, and María Candela Blanco from the…

6 hours ago

In crowded voice AI market, OpenAI bets on instruction-following and expressive speech to win enterprise adoption

OpenAI's new speech model, gpt-realtime, hopes that its more naturalistic voices would make enterprises use…

7 hours ago

Watch Our Livestream Replay: Back to School in the Age of AI

We explored our latest investigations into how tech is shaping education today.

7 hours ago