相关论文: Detecting Corpus-Level Knowledge Inconsistencies i…
The Internet has provided us with great opportunities for large scale collaborative public good projects. Wikipedia is a predominant example of such projects where conflicts emerge and get resolved through bottom-up mechanisms leading to…
Web-scale visual entity recognition, the task of associating images with their corresponding entities within vast knowledge bases like Wikipedia, presents significant challenges due to the lack of clean, large-scale training data. In this…
With more than 11 times as many pageviews as the next largest edition, English Wikipedia dominates global knowledge access relative to other language editions. Readers are prone to assuming English Wikipedia as a superset of all language…
Retrieval-augmented generation (RAG) frameworks enable large language models (LLMs) to retrieve relevant information from a knowledge base and incorporate it into the context for generating responses. This mitigates hallucinations and…
INTRODUCTION: Wikipedia is a major source of information, particularly for medical and health content, citing over 4 million scholarly publications. However, the representation of research-based knowledge across different languages on…
Millions of people irrespective of socioeconomic and demographic backgrounds, depend on Wikipedia articles everyday for keeping themselves informed regarding popular as well as obscure topics. Articles have been categorized by editors into…
Multilingual large-scale Pretrained Language Models (PLMs) have been shown to store considerable amounts of factual knowledge, but large variations are observed across languages. With the ultimate goal of ensuring that users with different…
In this paper we present statistical analysis of English texts from Wikipedia. We try to address the issue of language complexity empirically by comparing the simple English Wikipedia (Simple) to comparable samples of the main English…
Benchmarking modern large language models (LLMs) on complex and realistic tasks is critical to advancing their development. In this work, we evaluate the factual accuracy and citation performance of state-of-the-art LLMs on the task of…
Wikipedia plays a crucial role in the integrity of the Web. This work analyzes the reliability of this global encyclopedia through the lens of its references. We operationalize the notion of reference quality by defining reference need…
Factual consistency is one of the most important requirements when editing high quality documents. It is extremely important for automatic text generation systems like summarization, question answering, dialog modeling, and language…
The proliferation of fake news has had far-reaching implications on politics, the economy, and society at large. While Fake news detection methods have been employed to mitigate this issue, they primarily depend on two essential elements:…
Large language models (LLMs), despite their remarkable text generation capabilities, often hallucinate and generate text that is factually incorrect and not grounded in real-world knowledge. This poses serious risks in domains like…
Online encyclopediae like Wikipedia contain large amounts of text that need frequent corrections and updates. The new information may contradict existing content in encyclopediae. In this paper, we focus on rewriting such dynamically…
Benchmarks such as MMLU suggest flagship language models approach factuality saturation, with scores above 90\%. We show this picture is incomplete. \emph{LLMpedia} generates encyclopedic articles entirely from parametric memory, producing…
Information presented in Wikipedia articles must be attributable to reliable published sources in the form of references. This study examines over 5 million Wikipedia articles to assess the reliability of references in multiple language…
Our study identifies sentences in Wikipedia articles that are either identical or highly similar by applying techniques for near-duplicate detection of web pages. This is accomplished with a MapReduce implementation of minhash to identify…
Ensuring semantic consistency between source code and its accompanying comments is crucial for program comprehension, effective debugging, and long-term maintainability. Comment inconsistency arises when developers modify code but neglect…
A major challenge for many analyses of Wikipedia dynamics -- e.g., imbalances in content quality, geographic differences in what content is popular, what types of articles attract more editor discussion -- is grouping the very diverse range…
The different Wikipedia language editions vary dramatically in how comprehensive they are. As a result, most language editions contain only a small fraction of the sum of information that exists across all Wikipedias. In this paper, we…