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Found 12 papers, 3 papers with code
ViBe: A Text-to-Video Benchmark for Evaluating Hallucination in Large Multimodal Models
We introduce ViBe: a large-scale Text-to-Video Benchmark of hallucinated videos from T2V models.
Neurosymbolic AI approach to Attribution in Large Language Models
Attribution in large language models (LLMs) remains a significant challenge, particularly in ensuring the factual accuracy and reliability of the generated outputs.
Towards Infusing Auxiliary Knowledge for Distracted Driver Detection
Distracted driving is a leading cause of road accidents globally.
CausalLP: Learning causal relations with weighted knowledge graph link prediction
An evaluation of this approach uses a benchmark dataset of simulated videos for causal reasoning, CLEVRER-Humans, and compares the performance of multiple knowledge graph embedding algorithms.
FACTOID: FACtual enTailment fOr hallucInation Detection
We present FACTOID (FACTual enTAILment for hallucInation Detection), a benchmark dataset for FE.
"Sorry, Come Again?" Prompting -- Enhancing Comprehension and Diminishing Hallucination with [PAUSE]-injected Optimal Paraphrasing
We have fine-tuned an LLM with injected [PAUSE] tokens, allowing the LLM to pause while reading lengthier prompts.
Counter Turing Test CT^2: AI-Generated Text Detection is Not as Easy as You May Think -- Introducing AI Detectability Index
Given this cynosural spotlight on generative AI, AI-generated text detection (AGTD) has emerged as a topic that has already received immediate attention in research, with some initial methods having been proposed, soon followed by emergence of techniques to bypass detection.
The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations
Finally, to establish a method for quantifying and to offer a comparative spectrum that allows us to evaluate and rank LLMs based on their vulnerability to producing hallucinations, we propose Hallucination Vulnerability Index (HVI).
FACTIFY3M: A Benchmark for Multimodal Fact Verification with Explainability through 5W Question-Answering
To address this gap, we introduce FACTIFY 3M, a dataset of 3 million samples that pushes the boundaries of the domain of fact verification via a multimodal fake news dataset, in addition to offering explainability through the concept of 5W question-answering.
UBERT: A Novel Language Model for Synonymy Prediction at Scale in the UMLS Metathesaurus
The effectiveness of UBERT for UMLS Metathesaurus construction process is evaluated using the UMLS Vocabulary Alignment (UVA) task.
Machine learning for Internet of Things data analysis: A survey
This article assesses the different machine learning methods that deal with the challenges in IoT data by considering smart cities as the main use case.
CEVO: Comprehensive EVent Ontology Enhancing Cognitive Annotation
These use-cases demonstrate the benefits of using CEVO for annotation: (i) annotating English verbs from an abstract conceptualization, (ii) playing the role of an upper ontology for organizing ontological properties, and (iii) facilitating the annotation of text relations using any underlying vocabulary.
