Open-sourced large language models (LLMs) have exhibited remarkable performance in a
variety of NLP tasks, often catching up with the closed-sourced LLMs like ChatGPT. Among …

Reasoning is most powerful when an LLM accurately aggregates relevant information. We
examine the critical role of information aggregation in reasoning by requiring the LLM to …

Truthfulness stands out as an essential challenge for Large Language Models (LLMs).
Although many works have developed various ways for truthfulness enhancement, they …

Large language models (LLMs) have revolutionized various domains but still struggle with
non-Latin scripts and low-resource languages. This paper addresses the critical challenge …

Question answering on the hybrid context of tables and text (TATQA) is a critical task, with
broad applications in data-intensive domains. However, existing TATQA datasets are limited …

While reasoning and multilingual capabilities in Language Models (LMs) have achieved
remarkable progress in recent years, their integration into a unified paradigm, multilingual …

Evaluating large language models (LLMs) on their linguistic reasoning capabilities is an
important task to understand the gaps in their skills that may surface during large-scale …

Abstract LLM (Large Language Model) powered AI (Artificial Intelligence) assistants are a
popular tool used by programmers, but what impact do they have? In this thesis we …