4 citations · 9 across the 26 of their papers we have counts for
6 papers · 2 filters
Towards Global AI Inclusivity: A Large-Scale Multilingual Terminology Dataset (GIST)
Jiarui Liu, Iman Ouzzani, Wenkai Li +5
The field of machine translation has achieved significant advancements, yet domain-specific terminology translation, particularly in AI, remains challenging. We introduce GIST, a l…
BIG5-CHAT: Shaping LLM Personalities Through Training on Human-Grounded Data
Wenkai Li, Jiarui Liu, Andy Liu +3
In this work, we tackle the challenge of embedding realistic human personality traits into LLMs. Previous approaches have primarily focused on prompt-based methods that describe th…
Language Model Alignment in Multilingual Trolley Problems
Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti +9
We evaluate the moral alignment of LLMs with human preferences in multilingual trolley problems. Building on the Moral Machine experiment, which captures over 40 million human judg…
Automatic Generation of Model and Data Cards: A Step Towards Responsible AI
Jiarui Liu, Wenkai Li, Zhijing Jin +1
In an era of model and data proliferation in machine learning/AI especially marked by the rapid advancement of open-sourced technologies, there arises a critical need for standardi…
Analyzing the Role of Semantic Representations in the Era of Large Language Models
Zhijing Jin, Yuen Chen, Fernando Gonzalez +5
Traditionally, natural language processing (NLP) models often use a rich set of features created by linguistic expertise, such as semantic representations. However, in the era of l…
Implicit Personalization in Language Models: A Systematic Study
Zhijing Jin, Nils Heil, Jiarui Liu +5
Implicit Personalization (IP) is a phenomenon of language models inferring a user's background from the implicit cues in the input prompts and tailoring the response based on this…