4 citations · 5 across the 7 of their papers we have counts for
8 papers
Politically Speaking: LLMs on Changing International Affairs
Xuenan Cao, Wai Kei Chung, Ye Zhao +1
Ask your chatbot to impersonate an expert from Russia and an expert from US and query it on Chinese politics. How might the outputs differ? Or, to prepare ourselves for the worse,…
Advocate for Complete Benchmarks for Formal Reasoning with Formal/Informal Statements and Formal/Informal Proofs
Roozbeh Yousefzadeh, Xuenan Cao
This position paper provides a critical but constructive discussion of current practices in benchmarking and evaluative practices in the field of formal reasoning and automated the…
How Large Language Models (LLMs) Extrapolate: From Guided Missiles to Guided Prompts
Xuenan Cao
This paper argues that we should perceive LLMs as machines of extrapolation. Extrapolation is a statistical function for predicting the next value in a series. Extrapolation contri…
A Lean Dataset for International Math Olympiad: Small Steps towards Writing Math Proofs for Hard Problems
Roozbeh Yousefzadeh, Xuenan Cao, Azim Ospanov
Using AI to write formal proofs for mathematical problems is a challenging task that has seen some advancements in recent years. Automated systems such as Lean can verify the corre…
Towards a Scalable Reference-Free Evaluation of Generative Models
Azim Ospanov, Jingwei Zhang, Mohammad Jalali +3
While standard evaluation scores for generative models are mostly reference-based, a reference-dependent assessment of generative models could be generally difficult due to the una…
Large Language Models' Understanding of Math: Source Criticism and Extrapolation
Roozbeh Yousefzadeh, Xuenan Cao
It has been suggested that large language models such as GPT-4 have acquired some form of understanding beyond the correlations among the words in text including some understanding…
Should Machine Learning Models Report to Us When They Are Clueless?
Roozbeh Yousefzadeh, Xuenan Cao
The right to AI explainability has consolidated as a consensus in the research community and policy-making. However, a key component of explainability has been missing: extrapolati…
To what extent should we trust AI models when they extrapolate?
Roozbeh Yousefzadeh, Xuenan Cao
Many applications affecting human lives rely on models that have come to be known under the umbrella of machine learning and artificial intelligence. These AI models are usually co…