Survey of hallucination in natural language generation
Natural Language Generation (NLG) has improved exponentially in recent years thanks to
the development of sequence-to-sequence deep learning technologies such as Transformer …
the development of sequence-to-sequence deep learning technologies such as Transformer …
Towards trustworthy LLMs: a review on debiasing and dehallucinating in large language models
Z Lin, S Guan, W Zhang, H Zhang, Y Li… - Artificial Intelligence …, 2024 - Springer
Recently, large language models (LLMs) have attracted considerable attention due to their
remarkable capabilities. However, LLMs' generation of biased or hallucinatory content …
remarkable capabilities. However, LLMs' generation of biased or hallucinatory content …
A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions
The emergence of large language models (LLMs) has marked a significant breakthrough in
natural language processing (NLP), fueling a paradigm shift in information acquisition …
natural language processing (NLP), fueling a paradigm shift in information acquisition …
ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports
Objectives To assess the quality of simplified radiology reports generated with the large
language model (LLM) ChatGPT and to discuss challenges and chances of ChatGPT-like …
language model (LLM) ChatGPT and to discuss challenges and chances of ChatGPT-like …
Active retrieval augmented generation
Despite the remarkable ability of large language models (LMs) to comprehend and generate
language, they have a tendency to hallucinate and create factually inaccurate output …
language, they have a tendency to hallucinate and create factually inaccurate output …
Mitigating object hallucinations in large vision-language models through visual contrastive decoding
Abstract Large Vision-Language Models (LVLMs) have advanced considerably intertwining
visual recognition and language understanding to generate content that is not only coherent …
visual recognition and language understanding to generate content that is not only coherent …
Critic: Large language models can self-correct with tool-interactive critiquing
Recent developments in large language models (LLMs) have been impressive. However,
these models sometimes show inconsistencies and problematic behavior, such as …
these models sometimes show inconsistencies and problematic behavior, such as …
Generalized out-of-distribution detection: A survey
Abstract Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of
machine learning systems. For instance, in autonomous driving, we would like the driving …
machine learning systems. For instance, in autonomous driving, we would like the driving …
Truthfulqa: Measuring how models mimic human falsehoods
We propose a benchmark to measure whether a language model is truthful in generating
answers to questions. The benchmark comprises 817 questions that span 38 categories …
answers to questions. The benchmark comprises 817 questions that span 38 categories …
Structured denoising diffusion models in discrete state-spaces
Denoising diffusion probabilistic models (DDPMs)[Ho et al. 2021] have shown impressive
results on image and waveform generation in continuous state spaces. Here, we introduce …
results on image and waveform generation in continuous state spaces. Here, we introduce …