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cs.CL2026
Cognitive Agent Compilation for Explicit Problem Solver Modeling
Hyeongdon Moon, Carolyn Rosé, John Stamper
Large language models (LLMs) are widely used for tutoring, feedback generation, and content creation, but their broad pretraining makes them hard to constrain and poor substitutes…
cs.CL2026
ChartEditBench: Evaluating Grounded Multi-Turn Chart Editing in Multimodal Language Models
Manav Nitin Kapadnis, Lawanya Baghel, Atharva Naik +1
While Multimodal Large Language Models (MLLMs) perform strongly on single-turn chart generation, their ability to support real-world exploratory data analysis remains underexplored…
cs.CL2025
On Code-Induced Reasoning in LLMs
Abdul Waheed, Zhen Wu, Carolyn Rosé +1
Code data has been shown to enhance the reasoning capabilities of large language models (LLMs), but it remains unclear which aspects of code are most responsible. We investigate th…