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
Deep learning for anomaly detection: A review
Anomaly detection, aka outlier detection or novelty detection, has been a lasting yet active
research area in various research communities for several decades. There are still some …
research area in various research communities for several decades. There are still some …
Information retrieval: recent advances and beyond
This paper provides an extensive and thorough overview of the models and techniques
utilized in the first and second stages of the typical information retrieval processing chain …
utilized in the first and second stages of the typical information retrieval processing chain …
Chatbot arena: An open platform for evaluating llms by human preference
Large Language Models (LLMs) have unlocked new capabilities and applications; however,
evaluating the alignment with human preferences still poses significant challenges. To …
evaluating the alignment with human preferences still poses significant challenges. To …
Principled reinforcement learning with human feedback from pairwise or k-wise comparisons
We provide a theoretical framework for Reinforcement Learning with Human Feedback
(RLHF). We show that when the underlying true reward is linear, under both Bradley-Terry …
(RLHF). We show that when the underlying true reward is linear, under both Bradley-Terry …
Uncovering chatgpt's capabilities in recommender systems
The debut of ChatGPT has recently attracted significant attention from the natural language
processing (NLP) community and beyond. Existing studies have demonstrated that ChatGPT …
processing (NLP) community and beyond. Existing studies have demonstrated that ChatGPT …
Dense text retrieval based on pretrained language models: A survey
Text retrieval is a long-standing research topic on information seeking, where a system is
required to return relevant information resources to user's queries in natural language. From …
required to return relevant information resources to user's queries in natural language. From …
Large language models are effective text rankers with pairwise ranking prompting
Ranking documents using Large Language Models (LLMs) by directly feeding the query and
candidate documents into the prompt is an interesting and practical problem. However …
candidate documents into the prompt is an interesting and practical problem. However …
Large language models can accurately predict searcher preferences
P Thomas, S Spielman, N Craswell… - Proceedings of the 47th …, 2024 - dl.acm.org
Much of the evaluation and tuning of a search system relies on relevance labels---
annotations that say whether a document is useful for a given search and searcher. Ideally …
annotations that say whether a document is useful for a given search and searcher. Ideally …
Compositional exemplars for in-context learning
Large pretrained language models (LMs) have shown impressive In-Context Learning (ICL)
ability, where the model learns to do an unseen task simply by conditioning on a prompt …
ability, where the model learns to do an unseen task simply by conditioning on a prompt …
Learning to summarize with human feedback
As language models become more powerful, training and evaluation are increasingly
bottlenecked by the data and metrics used for a particular task. For example, summarization …
bottlenecked by the data and metrics used for a particular task. For example, summarization …