1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2026
Dynamic Context Evolution for Scalable Synthetic Data Generation
Ryan Lingo, Rajeev Chhajer
Large language models produce repetitive output when prompted independently across many batches, a phenomenon we term cross-batch mode collapse: the progressive loss of output dive…
cs.HC2025
Componentization: Decomposing Monolithic LLM Responses into Manipulable Semantic Units
Ryan Lingo, Rajeev Chhajer, Martin Arroyo +3
Large Language Models (LLMs) often produce monolithic text that is hard to edit in parts, which can slow down collaborative workflows. We present componentization, an approach that…
cs.CL2024★ 1 cited
Enhancing LLM Problem Solving with REAP: Reflection, Explicit Problem Deconstruction, and Advanced Prompting
Ryan Lingo, Martin Arroyo, Rajeev Chhajer
Large Language Models (LLMs) have transformed natural language processing, yet improving their problem-solving capabilities, particularly for complex, reasoning-intensive tasks, re…