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Found 12 papers, 6 papers with code
MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks
We develop an evaluation framework for MIMDE and introduce a novel set of complementary human and synthetic datasets to examine the potential of synthetic data for LLM evaluation.
Large language models can consistently generate high-quality content for election disinformation operations
Advances in large language models have raised concerns about their potential use in generating compelling election disinformation at scale.
Prompto: An open source library for asynchronous querying of LLM endpoints
Recent surge in Large Language Model (LLM) availability has opened exciting avenues for research.
Evidence of a log scaling law for political persuasion with large language models
Large language models can now generate political messages as persuasive as those written by humans, raising concerns about how far this persuasiveness may continue to increase with model size.
AI for bureaucratic productivity: Measuring the potential of AI to help automate 143 million UK government transactions
We estimate that UK central government conducts approximately one billion citizen-facing transactions per year in the provision of around 400 services, of which approximately 143 million are complex repetitive transactions.
Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal Data
These `cheaper' learning techniques hold significant potential for the social sciences, where development of large labelled training datasets is often a significant practical impediment to the use of machine learning for analytical tasks.
DoDo Learning: DOmain-DemOgraphic Transfer in Language Models for Detecting Abuse Targeted at Public Figures
We find that (i) small amounts of diverse data are hugely beneficial to generalisation and model adaptation; (ii) models transfer more easily across demographics but models trained on cross-domain data are more generalisable; (iii) some groups contribute more to generalisability than others; and (iv) dataset similarity is a signal of transferability.
Understanding Counterspeech for Online Harm Mitigation
Counterspeech offers direct rebuttals to hateful speech by challenging perpetrators of hate and showing support to targets of abuse.
'Team-in-the-loop': Ostrom's IAD framework 'rules in use' to map and measure contextual impacts of AI
This article explores how the 'rules in use' from Ostrom's Institutional Analysis and Development Framework (IAD) can be developed as a context analysis approach for AI.
A multidomain relational framework to guide institutional AI research and adoption
Calls for new metrics, technical standards and governance mechanisms to guide the adoption of Artificial Intelligence (AI) in institutions and public administration are now commonplace.
Artificial intelligence in government: Concepts, standards, and a unified framework
Recent advances in artificial intelligence (AI), especially in generative language modelling, hold the promise of transforming government.
How do climate change skeptics engage with opposing views? Understanding mechanisms of social identity and cognitive dissonance in an online forum
Users who engaged with dissonant submissions were also more likely to return to the forum.
Social and Information Networks Computers and Society
