Showing cs.AIShow all
3 papers · 1 filter
cs.AI2026
Efficient Reasoning via Constrained Optimization in Latent Space
Zhinan Hou, Xingchen Li, XingChen Li +1
Large Reasoning Models (LRMs) have shown remarkable reasoning capabilities, yet they still suffer from overthinking, generating redundant reasoning steps which incur substantial to…
cs.AI2026
What Matters in On-Policy Distillation? A Perspective on Data Efficiency and Data Selection
Zhinan Hou, Jiaqi Zhang, Xunliang Cai +1
On-Policy Distillation (OPD) has emerged as a widely adopted post-training paradigm for enhancing large language models in reasoning domains. However, the data-centric mechanisms i…
cs.AI2026
LLM4Branch: Large Language Model for Discovering Efficient Branching Policies of Integer Programs
Zhinan Hou, Xingchen Li, Yankai Zhang +2
Efficient branching policies are essential for accelerating Mixed Integer Linear Programming (MILP) solvers. Their design has long relied on hand-crafted heuristics, and now machin…