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Large language models for data annotation and synthesis: A survey
Data annotation and synthesis generally refers to the labeling or generating of raw data with
relevant information, which could be used for improving the efficacy of machine learning …
relevant information, which could be used for improving the efficacy of machine learning …
Counterfactual debating with preset stances for hallucination elimination of llms
Large Language Models (LLMs) excel in various natural language processing tasks but
struggle with hallucination issues. Existing solutions have considered utilizing LLMs' …
struggle with hallucination issues. Existing solutions have considered utilizing LLMs' …
Did you tell a deadly lie? evaluating large language models for health misinformation identification
The rapid spread of health misinformation online poses significant challenges to public
health, potentially leading to confusion, undermining trust in health authorities, and …
health, potentially leading to confusion, undermining trust in health authorities, and …
[PDF][PDF] SINAI participation in SimpleText task 2 at CLEF 2024: zero-shot prompting on GPT-4-turbo for lexical complexity prediction
J Ortiz-Zambrano, C Espin-Riofrio… - Working Notes of the …, 2024 - ceur-ws.org
In this article, we present our participation in Tasks 2.1 and 2.2 of the SimpleText track of
CLEF 2024. Our work focused on the implementation of zero-shot learning using the GPT-4 …
CLEF 2024. Our work focused on the implementation of zero-shot learning using the GPT-4 …
Estimating Causal Effects of Text Interventions Leveraging LLMs
Quantifying the effect of textual interventions in social systems, such as reducing anger in
social media posts to see its impact on engagement, poses significant challenges. Direct …
social media posts to see its impact on engagement, poses significant challenges. Direct …
FitCF: A Framework for Automatic Feature Importance-guided Counterfactual Example Generation
Counterfactual examples are widely used in natural language processing (NLP) as valuable
data to improve models, and in explainable artificial intelligence (XAI) to understand model …
data to improve models, and in explainable artificial intelligence (XAI) to understand model …
Interpreting Language Reward Models via Contrastive Explanations
Reward models (RMs) are a crucial component in the alignment of large language
models'(LLMs) outputs with human values. RMs approximate human preferences over …
models'(LLMs) outputs with human values. RMs approximate human preferences over …
SCENE: Evaluating Explainable AI Techniques Using Soft Counterfactuals
H Zheng, U Pamuksuz - arxiv preprint arxiv:2408.04575, 2024 - arxiv.org
Explainable Artificial Intelligence (XAI) plays a crucial role in enhancing the transparency
and accountability of AI models, particularly in natural language processing (NLP) tasks …
and accountability of AI models, particularly in natural language processing (NLP) tasks …
Large language models and causal analysis: zero-shot counterfactuals in hate speech perception
S Hernández Jiménez - 2024 - diposit.ub.edu
[en] Detecting hate speech is crucial for maintaining the integrity of social media platforms,
as it involves identifying content that denigrates individuals or groups based on their …
as it involves identifying content that denigrates individuals or groups based on their …