Loki: An Open-Source Tool for Fact Verification
We introduce Loki, an open-source tool designed to address the growing problem of misinformation. Loki adopts a human-centered approach, striking a balance between the quality of fact-checking and the cost of human involvement. It decomposes the fact-checking task into a five-step pipeline: breaking down long texts into individual claims, assessing their check-worthiness, generating queries, retrieving evidence, and verifying the claims. Instead of fully automating the claim verification process, Loki provides essential information at each step to assist human judgment, especially for general users such as journalists and content moderators. Moreover, it has been optimized for latency, robustness, and cost efficiency at a commercially usable level. Loki is released under an MIT license and is available on GitHub. We also provide a video presenting the system and its capabilities.
Code (1)
Tasks
Claim VerificationFact CheckingFact VerificationMisinformationSimilar Papers 제목 키워드 기반
LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models
With the rapid development of AI-generated content, the future internet may be inundated with synthetic data, making the discrimination of authentic and credible multimodal data increasingly challenging. Synthetic data d…
Multiple-choicePractical Data Poisoning Attack against Next-Item Recommendation
Online recommendation systems make use of a variety of information sources to provide users the items that users are potentially interested in. However, due to the openness of the online platform, recommendation systems …
Data PoisoningRecommendation SystemsReinforcement LearningFast Policy Learning through Imitation and Reinforcement
Imitation learning (IL) consists of a set of tools that leverage expert demonstrations to quickly learn policies. However, if the expert is suboptimal, IL can yield policies with inferior performance compared to reinforc…
Imitation LearningReinforcement LearningReinforcement Learning (RL)Online Multimedia Verification with Computational Tools and OSINT: Russia-Ukraine Conflict Case Studies
This paper investigates the use of computational tools and Open-Source Intelligence (OSINT) techniques for verifying online multimedia content, with a specific focus on real-world cases from the Russia-Ukraine conflict. …
MisinformationLokiLM: Technical Report
In this work, we introduce LokiLM, a 1.4B parameter large language model trained on 500B tokens. Our model performs strongly in natural language reasoning tasks and achieves state-of-the-art performance among models with…
Knowledge DistillationLanguage ModelingLanguage ModellingLarge Language Model+1