First systematic test shows activation steering robustness drops sharply (up to 64%) under adversarial input perturbations across multiple extraction methods, models, and personas.
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8 Pith papers cite this work, alongside 775 external citations. Polarity classification is still indexing.
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SMX explains spectral ML classifiers by summarizing expert zones with PCA, testing quantile predicates via perturbation, aggregating via directed graph centrality, and reconstructing thresholds back onto original spectra.
Data-similarity and data-influence produce significantly overlapping rankings of training documents for LLM outputs, with asymmetry allowing a favorable cost-accuracy trade-off.
Arbor combines a coordinator, executors, and a hypothesis tree to enable cumulative autonomous research, outperforming Codex and Claude Code by over 2.5x on six real tasks and reaching 86.36% Any Medal on MLE-Bench Lite.
Synthetically formalizing information needs into topics with descriptions and narratives improves LLM relevance assessor agreement with humans and reduces over-labeling of relevant documents on TREC Deep Learning and Robust04.
Relative Probability Association Metric (RPAM) measures LM associations via softmax-normalized continuation probabilities and correlates strongly with human associations and downstream LM behavior across three models.
Young adults engage with low-quality news content on social media despite stating preferences for high-quality, accurate, and diverse information, and they produce higher-quality feeds when curating for a hypothetical persona.
Visibility in generative AI search must be assessed as a distribution over repeated measurements rather than single queries because outputs vary across runs, prompts, and time.
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Formalized Information Needs Improve Large-Language-Model Relevance Judgments
Synthetically formalizing information needs into topics with descriptions and narratives improves LLM relevance assessor agreement with humans and reduces over-labeling of relevant documents on TREC Deep Learning and Robust04.
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Understanding the Gap Between Stated and Revealed Preferences in News Curation: A Study of Young Adult Social Media Users
Young adults engage with low-quality news content on social media despite stating preferences for high-quality, accurate, and diverse information, and they produce higher-quality feeds when curating for a hypothetical persona.