西湖大学联合国内外十家科研单位发表了一篇大模型事实性的综述《Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity》,该综述调研了三百余篇文献,重点讨论了事实性的定义和影响、大模型事实性的评估、大模型事实性机制和产生错误的原理、大模型事实性的增强等几个方面的内容,...
Factuality Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment, arXiv 2023.08 [Paper] Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity, arXiv 2023.10 [Paper] [GitHub] ...
LLM-Factuality-Survey The repository for the survey paper "Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity" Cunxiang Wang1,7*, Xiaoze Liu2*, Yuanhao Yue3*, Qipeng Guo4, Xiangkun Hu4, Xiangru Tang5, Tianhang Zhang6, Cheng Jiayang7, Yunzhi Yao8, ...
In: Proceedings of the 36th Conference on Neural Information Processing Systems. 2022, 24824–24837 Kojima T, Gu S S, Reid M, Matsuo Y, Iwasawa Y. Large language models are zero-shot reasoners. In: Proceedings of the 36th Conference on Neural Information Processing Systems. 2022, 22199–...
2022. Factuality enhanced language models for open-ended text generation. arXiv preprint arXiv:2206.04624 (2022). 暴露偏差:训练和测试阶段不匹配的exposure bias问题可能导致LLMs出现幻觉,特别是生成long-form response的时候。 Chaojun Wang and Rico Sennrich. 2020. On exposure bias, hallucination and ...
In this survey, we provide such systematic and comprehensive literature review of 175 research papers while focusing on textual credibility signals and Natural Language Processing (NLP), which undergoes a significant advancement due to Large Language Models (LLMs). While positioning the NLP research ...
With the continual expansion in the size of language models, large language models (LLMs) have exhibited noteworthy performance under both zero- and few-shot settings, rivaling fine-tuned pre-trained models. This shift has precipitated a transformation in the evaluation landscape, marking a departure...
As Large Language Models (LLMs) become popular, there emerged an important trend of using multimodality to augment the LLMs' generation ability, which enables LLMs to better interact with the world. However, there lacks a unified perception of at which stage and how to incorporate different mod...
Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv 11 Oct 2023 Paper A Survey on Large Language Models for Personalized and Explainable Recommendations arXiv 21 Nov 2023 Paper Adaptation Tuning Bridging the Gap: A Survey on Integrating (Human) Feedback ...
Llm-planner: Few-shot grounded planning for embodied agents with large language models. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. 2023, 2998–3009 61. Huang W, Xia F, Xiao T, Chan H, Liang J, Florence P, Zeng A, Tompson J, Mordatch I, Chebotar Y,...