#factuality — Public Fediverse posts

🚨 We're hiring!
As part of the ARMADA MSCA Doctoral Network, my group at #TUWien is offering a fully funded PhD position on:
➡️ Knowledge-Graph driven Factuality and Explainability

📍 Based in Vienna, Austria
🌍 Includes secondments, training schools, and a strong European research network
📅 Apply by: June 30, 2025 (mobility rules apply)

Details and how to apply:
👉 https://dmki-tuwien.github.io/jobs.html#armada
🌐 Full ARMADA call with all 15 PhD topics: https://armada-dn.eu/call

#LLM #KnowledgeGraphs #Factuality

GitHub - Libr-AI/ #OpenFactVerification

#Loki is our open-source solution designed to automate the process of verifying #factuality. It provides a comprehensive pipeline for dissecting long texts into individual claims, assessing their worthiness for #verification, generating queries for evidence search, crawling for evidence, and ultimately verifying the claims

> interesting, does anyone have any experience with this tool?
#ai

https://github.com/Libr-AI/OpenFactVerification

How can we improve LM factuality and editability with nothing but the LM itself?

Introducing Deductive Closure Training (DCT):

1. generate statements and their implications
2. identify a logically consistent subset
3. distill this subset back to LM

https://lingo-mit.github.io/deductive-closure/

#NLP #modelEditing #LLM #LLMs #data #bias #factuality

See the sheer joy of my collaborators at #ACL2023 when 🤩
DissentQA
won best Paper AC award

This is a happy outcome of the fruitful collaboration with a group of wonderfully friendly people

https://arxiv.org/abs/2211.05655
#nlproc #machinelearning #Qa #factuality

False Promise of Imitating Proprietary LLMs: new paper argues that open source models imitating ChatGPT are less successful than perceived by human assessors because of imitating LLM style more successfully than content. Implies a need for more pre-training data, & improved evaluation data & method.
https://arxiv.org/pdf/2305.15717.pdf
#LLM #OpenSource #factuality #evaluation #assessment #chatgpt #AI #imitation #training #data #MachineLearning #safety #toxicity @machinelearning