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This PNAS study of 7.3 million academic papers finds that by 2025, over half show LLM influence, with significant inequality in adoption across lower-prestige and non-English institutions.
This paper analyzes 20,574 real-world coding-agent sessions to identify how AI agents misalign with developer intent, finding that constraint violations and inaccurate self-reporting are the most common failure modes, imposing trust and effort costs rather than irreversible damage.