Moral Scenarios
9 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Moral Scenarios
| Trend | Dataset | Best Model | Paper | Code | Compare |
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BIG-bench
OllaBench v.0.2
Most implemented papers
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
"Oops, Did I Just Say That?" Testing and Repairing Unethical Suggestions of Large Language Models with Suggest-Critique-Reflect Process
Moreover, we propose a novel on-the-fly (OTF) repairing scheme that repairs unethical suggestions made by LLMs in real-time.
Evaluating the Moral Beliefs Encoded in LLMs
(2) We apply this method to study what moral beliefs are encoded in different LLMs, especially in ambiguous cases where the right choice is not obvious.
MOKA: Moral Knowledge Augmentation for Moral Event Extraction
News media often strive to minimize explicit moral language in news articles, yet most articles are dense with moral values as expressed through the reported events themselves.
SaGE: Evaluating Moral Consistency in Large Language Models
vnnm404/SaGE
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To this extent, we construct the Moral Consistency Corpus (MCC), containing 50K moral questions, responses to them by LLMs, and the RoTs that these models followed.
CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Models
These help us curate CMoralEval that encompasses both explicit moral scenarios (14, 964 instances) and moral dilemma scenarios (15, 424 instances), each with instances from different data sources.
M$^3$oralBench: A MultiModal Moral Benchmark for LVLMs
To bridge this gap, we introduce M$^3$oralBench, the first MultiModal Moral Benchmark for LVLMs.
Measurement of LLM's Philosophies of Human Nature
The widespread application of artificial intelligence (AI) in various tasks, along with frequent reports of conflicts or violations involving AI, has sparked societal concerns about interactions with AI systems.
HALO: Hierarchical Autonomous Logic-Oriented Orchestration for Multi-Agent LLM Systems
Notably, HALO achieves up to 13. 3% performance gain on the Moral Scenarios subject in the MMLU benchmark and up to 19. 6% performance gain on the Algebra subarea in the MATH benchmark, indicating its advanced proficiency in tackling highly specialized and expert-level tasks.
