Guang Zhang
2 indexed papers
Recent (6 mo)
2With code
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226
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NLP×2AI×1
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Research Timeline
2026
D$^3$: Dynamic Directional Graph-Constrained Data Scheduling for LLM Training
The paper proposes $D^3$, a dynamic graph-constrained scheduling framework that optimizes LLM training order by modeling sample interactions as a dynamic influence graph.
Towards Efficient LLMs Annealing with Principled Sample Selection
The paper proposes DiReCT, a novel framework that treats data selection during LLM annealing as a constrained optimization problem based on the spectral geometry of the loss landscape, achieving state-of-the-art performance.
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Papers
cs.CLcs.AIRecentMay 29, 2026
D$^3$: Dynamic Directional Graph-Constrained Data Scheduling for LLM Training
The paper proposes $D^3$, a dynamic graph-constrained scheduling framework that optimizes LLM training order by modeling sample interactions as a dynamic influence graph.
View →
cs.CLRecentMay 29, 2026