Data-similarity and data-influence produce significantly overlapping rankings of training documents for LLM outputs, with asymmetry allowing a favorable cost-accuracy trade-off.
and Tsvetkov, Yulia
4 Pith papers cite this work. Polarity classification is still indexing.
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Interpretability research should be judged by actionability—the degree to which its insights support concrete decisions and interventions—rather than explanatory power alone.
Rigorous interpretability can function as a principled form of model evaluation if its claims are falsifiable, reproducible, and predictive.
Pretrained and fine-tuned Qwen3 embeddings exhibit measurable alignment with an expert symptom matrix via RSA on Reddit mental-health data, strengthened by fine-tuning at fine-grained levels and larger scale, with residual alignment after VAD/LIWC/topic controls.
citing papers explorer
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Quantifying the Agreement Between Data-Influence and Data-Similarity to Understand LLM Behavior
Data-similarity and data-influence produce significantly overlapping rankings of training documents for LLM outputs, with asymmetry allowing a favorable cost-accuracy trade-off.
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Rigorous Interpretation Is a Form of Evaluation
Rigorous interpretability can function as a principled form of model evaluation if its claims are falsifiable, reproducible, and predictive.
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Do LLM Embedding Spaces Recover Expert Structure?
Pretrained and fine-tuned Qwen3 embeddings exhibit measurable alignment with an expert symptom matrix via RSA on Reddit mental-health data, strengthened by fine-tuning at fine-grained levels and larger scale, with residual alignment after VAD/LIWC/topic controls.