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New research maps origins of social reasoning in language models

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a method to understand the origins of social reasoning capabilities in language models by analyzing their training data. Using gradient-based attribution on the Dolma3 dataset, they mapped specific regions of the corpus that contribute to social versus STEM reasoning. The study found that social and STEM reasoning draw from distinct data sources, with reasoning capabilities being more sensitive to these distinctions than factual knowledge. Targeted unlearning experiments partially validated these findings by showing that removing high-attribution data bins degraded aligned benchmarks. AI

IMPACT Provides a new method for understanding model behavior and potentially improving training data curation for specialized reasoning skills.

RANK_REASON The cluster contains an academic paper detailing a new methodology for analyzing language model capabilities.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New research maps origins of social reasoning in language models

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The cluster contains an academic paper detailing a new methodology for analyzing language model capabilities.
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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Glenn Matlin, Chandreyi Chakraborty, Saehee Eom, Mika Okamoto, Rayan Castilla, Louis Jaburi, Alvin Deng, Taywon Min, Lucia Quirke, Stella Biderman, Mark Riedl ·

    Where Does Social Reasoning Come From? Capability Provenance in Language Models

    arXiv:2606.19625v1 Announce Type: new Abstract: We use training-data attribution as an interpretable tool for capability discovery, mapping which regions of the pretraining corpus support social-reasoning versus STEM-reasoning in OLMo3-7B. Training-data attribution measures how s…

  2. arXiv cs.CL TIER_1 English(EN) · Mark Riedl ·

    Where Does Social Reasoning Come From? Capability Provenance in Language Models

    We use training-data attribution as an interpretable tool for capability discovery, mapping which regions of the pretraining corpus support social-reasoning versus STEM-reasoning in OLMo3-7B. Training-data attribution measures how strongly each training document influences a mode…

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