Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Give us the facts: Enhancing large language models with knowledge graphs for fact-aware language modeling
Recently, ChatGPT, a representative large language model (LLM), has gained considerable
attention. Due to their powerful emergent abilities, recent LLMs are considered as a possible …
attention. Due to their powerful emergent abilities, recent LLMs are considered as a possible …
Datasets for large language models: A comprehensive survey
This paper embarks on an exploration into the Large Language Model (LLM) datasets,
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …
[PDF][PDF] Language model behavior: A comprehensive survey
Transformer language models have received widespread public attention, yet their
generated text is often surprising even to NLP researchers. In this survey, we discuss over …
generated text is often surprising even to NLP researchers. In this survey, we discuss over …
ROBBIE: Robust bias evaluation of large generative language models
As generative large language models (LLMs) grow more performant and prevalent, we must
develop comprehensive enough tools to measure and improve their fairness. Different …
develop comprehensive enough tools to measure and improve their fairness. Different …
Evaluating large language models in theory of mind tasks
M Kosinski - Proceedings of the National Academy of Sciences, 2024 - pnas.org
Eleven large language models (LLMs) were assessed using 40 bespoke false-belief tasks,
considered a gold standard in testing theory of mind (ToM) in humans. Each task included a …
considered a gold standard in testing theory of mind (ToM) in humans. Each task included a …
A causal explainable guardrails for large language models
Large Language Models (LLMs) have shown impressive performance in natural language
tasks, but their outputs can exhibit undesirable attributes or biases. Existing methods for …
tasks, but their outputs can exhibit undesirable attributes or biases. Existing methods for …
Adversarial Attacks on Large Language Model‐Based System and Mitigating Strategies: A Case Study on ChatGPT
Machine learning algorithms are at the forefront of the development of advanced information
systems. The rapid progress in machine learning technology has enabled cutting‐edge …
systems. The rapid progress in machine learning technology has enabled cutting‐edge …
Give me the facts! a survey on factual knowledge probing in pre-trained language models
Pre-trained Language Models (PLMs) are trained on vast unlabeled data, rich in world
knowledge. This fact has sparked the interest of the community in quantifying the amount of …
knowledge. This fact has sparked the interest of the community in quantifying the amount of …
The life cycle of knowledge in big language models: A survey
Abstract Knowledge plays a critical role in artificial intelligence. Recently, the extensive
success of pre-trained language models (PLMs) has raised significant attention about how …
success of pre-trained language models (PLMs) has raised significant attention about how …
Aligning as debiasing: Causality-aware alignment via reinforcement learning with interventional feedback
Large language models (LLMs) often generate biased outputs containing offensive, toxic, or
stereotypical text. Existing LLM alignment methods such as reinforcement learning from …
stereotypical text. Existing LLM alignment methods such as reinforcement learning from …