Papers by Philip Schroeder

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Challenge:	Large language models (LLMs) have shown impressive capabilities across diverse settings, but their performance degrades as context length and complexity increases.
Approach:	They propose to frame model generation as a thread of execution that, based on the context, can run to completion or dynamically spawn new threads.
Outcome:	The proposed model outperforms existing frameworks by 10% to 50% on diverse benchmarks.