Dynamic Sampling that Adapts: Self-Aware Iterative Data Persistent Optimization for Mathematical Reasoning (2026 · 4 citations)
Data selection for training math-reasoning LLMs usually depends on fixed difficulty labels or external scorers.
MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis (2026 · 3 citations)
Synthetic data for mathematical reasoning is often built either by mutating human-curated seed problems, which limits diversity to the seeds' scope, or by prompting models from scratch, which tends toward repetitive, shallow problems (mode collapse).
Why Did Apple Fall: Evaluating Curiosity in Large Language Models (2026 · 1 citation)
Curiosity-inspired intrinsic rewards are increasingly used in RL training of LLMs, but it has not been checked whether these models actually behave in curious ways, or whether the reported gains simply come from amplified statistical signals such as entropy.
Memory-Guided Hard Data Augmentation for Multimodal Named Entity Recognition (2026)
The paper targets data augmentation for Multimodal Named Entity Recognition (MNER), where images help disambiguate text.

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Papers of our library cite their works 5 times (of the 149,439 papers whose bibliographies we read); 3 citing papers with a page here →.

Updated 1 November 2026