Large language models are temporal and causal reasoners for video question answering

D Ko, JS Lee, W Kang, B Roh, HJ Kim - arXiv preprint arXiv:2310.15747, 2023 - arxiv.org
Large Language Models (LLMs) have shown remarkable performances on a wide range of
natural language understanding and generation tasks. We observe that the LLMs provide …

Legal syllogism prompting: Teaching large language models for legal judgment prediction

C Jiang, X Yang - … of the Nineteenth International Conference on …, 2023 - dl.acm.org
Legal syllogism is a form of deductive reasoning commonly used by legal professionals to
analyze cases. In this paper, we propose legal syllogism prompting (LoT), a simple …

Taking advice from chatgpt

P Zhang - arXiv preprint arXiv:2305.11888, 2023 - arxiv.org
A growing literature studies how humans incorporate advice from algorithms. This study
examines an algorithm with millions of daily users: ChatGPT. In a preregistered study, 118 …

Can language models teach? teacher explanations improve student performance via personalization

S Saha, P Hase, M Bansal - Advances in Neural …, 2024 - proceedings.neurips.cc
A hallmark property of explainable AI models is the ability to teach other agents,
communicating knowledge of how to perform a task. While Large Language Models (LLMs) …

Human-LLM collaborative annotation through effective verification of LLM labels

X Wang, H Kim, S Rahman, K Mitra… - Proceedings of the CHI …, 2024 - dl.acm.org
Large language models (LLMs) have shown remarkable performance across various natural
language processing (NLP) tasks, indicating their significant potential as data annotators …

Explaincpe: A free-text explanation benchmark of chinese pharmacist examination

D Li, J Yu, B Hu, Z Xu, M Zhang - arXiv preprint arXiv:2305.12945, 2023 - arxiv.org
As ChatGPT and GPT-4 spearhead the development of Large Language Models (LLMs),
more researchers are investigating their performance across various tasks. But more …

Explainable Generative AI (GenXAI): A Survey, Conceptualization, and Research Agenda

J Schneider - arXiv preprint arXiv:2404.09554, 2024 - arxiv.org
Generative AI (GenAI) marked a shift from AI being able to recognize to AI being able to
generate solutions for a wide variety of tasks. As the generated solutions and applications …

Can language models teach weaker agents? teacher explanations improve students via personalization

S Saha, P Hase, M Bansal - … of the 37th International Conference on …, 2023 - dl.acm.org
A hallmark property of explainable AI models is the ability to teach other agents,
communicating knowledge of how to perform a task. While Large Language Models (LLMs) …

Simple framework for interpretable fine-grained text classification

M Battogtokh, M Luck, C Davidescu… - European Conference on …, 2023 - Springer
Fine-grained text classification with similar and many labels is a challenge in practical
applications. Interpreting predictions in this context is particularly difficult. To address this …

[PDF][PDF] Interpretable and Controllable Language Models

P Hase - 2024 - peterbhase.github.io
The field of machine learning has reached the point where learning systems now
accomplish complicated tasks that we cannot ourselves describe algorithmic solutions to …