Who cites «MASPO: Unifying Gradient Utilization, Probability Mass, and Signal Reliability for Robust and Sample-Efficient LLM Reasoning»
- Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM UnlearningAnnual Meeting of the Association for Computational Linguistics (ACL)Naixin Zhai, Pengyang Shao, Binbin Zheng, et al.2026 · 2 citations
- Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search TrajectoriesAnnual Meeting of the Association for Computational Linguistics (ACL)Peiyang Liu, Zhirui Chen, Xi Wang, et al.2026 · 1 citation
- WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Rui Wang, Ce Zhang, Jun-Yu Ma, et al.2026 · 1 citation
This page in Markdown → https://md.research.elamur.ai/free/en/papers/fu-2026-maspo-unifying-gradient-utilization-probability/cited-by/