27 citations · 47 across the 9 of their papers we have counts for
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cs.CL2026
TokenGate: Adapting LLMs for Fast and Memory-Efficient Prefill with Learned Token Pruning
Liana Patel, Rishabh Ranjan, Ion Stoica +2
Expert human readers process large inputs (e.g., code repositories and long documents) by skimming to closely read only what matters. On the other hand, language models process all…
cs.DB2026
What Happens When the Model Eats the Stack? Rethinking the Research Agenda for Data Agents to Withstand the Bitter Lesson
Liana Patel, Siddharth Jha, Negar Arabzadeh +3
The bitter lesson poses an existential question for the data systems community, whereby large language models (LLMs) trained end-to-end are rapidly internalizing new capabilities t…