This work studies mitigating fact-conflicting hallucinations for large language model (LLM) at
inference time. Particularly, we propose a self-endorsement framework that leverages the …

Decoding methods for large language models (LLMs) usually struggle with the tradeoff
between ensuring factuality and maintaining diversity. For example, a higher p threshold in …

Foundation models, such as large language models (LLMs) and large vision-language
models (LVLMs), have gained significant attention for their remarkable performance across …