8 papers
Detecting Corpus-Level Knowledge Inconsistencies in Wikipedia with Large Language Models
Sina J. Semnani, Jirayu Burapacheep, Arpandeep Khatua +3
Wikipedia is the largest open knowledge corpus, widely used worldwide and serving as a key resource for training large language models (LLMs) and retrieval-augmented generation (RA…
CHURRO: Making History Readable with an Open-Weight Large Vision-Language Model for High-Accuracy, Low-Cost Historical Text Recognition
Sina J. Semnani, Han Zhang, Xinyan He +2
Accurate text recognition for historical documents can greatly advance the study and preservation of cultural heritage. Existing vision-language models (VLMs), however, are designe…
LEMONADE: A Large Multilingual Expert-Annotated Abstractive Event Dataset for the Real World
Sina J. Semnani, Pingyue Zhang, Wanyue Zhai +6
This paper presents LEMONADE, a large-scale conflict event dataset comprising 39,786 events across 20 languages and 171 countries, with extensive coverage of region-specific entiti…
Zero-shot Persuasive Chatbots with LLM-Generated Strategies and Information Retrieval
Kazuaki Furumai, Roberto Legaspi, Julio Vizcarra +6
Persuasion plays a pivotal role in a wide range of applications from health intervention to the promotion of social good. Persuasive chatbots employed responsibly for social good c…
SPINACH: SPARQL-Based Information Navigation for Challenging Real-World Questions
Shicheng Liu, Sina J. Semnani, Harold Triedman +3
Large Language Models (LLMs) have led to significant improvements in the Knowledge Base Question Answering (KBQA) task. However, datasets used in KBQA studies do not capture the tr…
Into the Unknown Unknowns: Engaged Human Learning through Participation in Language Model Agent Conversations
Yucheng Jiang, Yijia Shao, Dekun Ma +2
While language model (LM)-powered chatbots and generative search engines excel at answering concrete queries, discovering information in the terrain of unknown unknowns remains cha…