6 citations · 6 across the 11 of their papers we have counts for
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cs.CL2026
Better, Faster, Stronger: Programmatic Skill Learning Best Reduces Agent Cost
Zixi Huang, Xiheng Wang, Andrew Wang +4
Recently, the practice of augmenting LLM agent capability with skills has gained prevalence. We explore the cost effective adaptation of agents to novel domains by means of learnin…
cs.CL2026
Inducing Artificial Uncertainty in Language Models
Sophia Hager, Simon Zeng, Nicholas Andrews
In safety-critical applications, language models should be able to characterize their uncertainty with meaningful probabilities. Many uncertainty quantification approaches require…
cs.CL2026
Can Coding Agents Reproduce Findings in Computational Materials Science?
Ziyang Huang, Yi Cao, Ali K. Shargh +15
Large language models are increasingly deployed as autonomous coding agents and have achieved remarkably strong performance on software engineering benchmarks. However, it is uncle…