KODIS: A multicultural dispute resolution dialogue corpus

A dyadic dispute resolution corpus containing thousands of dialogues from over 75 countries.

NAACL

April 29, 2025

Topics:

Reinforcement Learning Natural-Language Processing (NLP)Account Takeover

We present KODIS, a dyadic dispute resolution corpus containing thousands of dialogues from over 75 countries. Motivated by a theoretical model of culture and conflict, participants engage in a typical customer service dispute designed by experts to evoke strong emotions and conflict. The corpus contains a rich set of dispositional, process, and outcome measures. The initial analysis supports theories of how anger expressions lead to escalatory spirals and highlights cultural differences in emotional expression. We make this corpus and data collection framework available to the community.

Latest publications

ProxyLM: predicting language model performance on multilingual tasks via proxy models

A scalable framework using proxy models to efficiently predict the performance of multilingual language models on NLP tasks.

Retrieval-Augmented Generation (RAG)

Natural-Language Processing (NLP)

Retrieval-Augmented Generation (RAG)

WorldCuisines: a massive-scale benchmark for multilingual and multicultural visual question answering on global cuisines

A massive multilingual and multicultural visual question answering benchmark for evaluating VLMs on global cuisines.

Out-of-Distribution Detection (OOD)

Reinforcement Learning

Vision-Language Models (VLMs)

Out-of-Distribution Detection (OOD)

Building safe GenAI applications: An end-to-end overview of red teaming for Large Language Models

A survey covering attack methods, evaluation, metrics, and tools for identifying and mitigating GenAI application vulnerabilities.

Large Language Models (LLMs)

Large Language Models (LLMs)