15 citations · 33 across the 10 of their papers we have counts for
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cs.AI2026
Agents Learn Their Runtime: Interpreter Persistence as Training-Time Semantics
Victor May, Aaditya Salgarkar, Yishan Wang +2
Tool-augmented LLMs are increasingly deployed as agents that interleave natural-language reasoning with executable Python actions, as in CodeAct-style frameworks. In deployment, th…
cs.AI2024★ 4 cited
Bridging the Data Provenance Gap Across Text, Speech and Video
Shayne Longpre, Nikhil Singh, Manuel Cherep +40
Progress in AI is driven largely by the scale and quality of training data. Despite this, there is a deficit of empirical analysis examining the attributes of well-established data…