2 citations · 2 across the 7 of their papers we have counts for
9 papers
AIM-ZO: Activation-Informed Subspace Maintenance for Zeroth-Order LLM Fine-Tuning
Yue Xie, Zhi Zheng, Yunpeng Ba +5
Zeroth-order (ZO) optimization offers a memory-efficient alternative for LLM fine-tuning by estimating updates only from forward evaluations of perturbed parameters, without backpr…
GraphSkillEvo: Evolutionary Optimization of Graph-Structured Agent Skills
Rui Sun, Zhi Zheng, Zhenkun Wang +1
Skills can improve the performance of Large Language Model (LLM) agents by providing task-specific procedural guidance, while skill optimization further improves their effectivenes…
Understanding Evolution Strategies for LLM Reasoning: Broader Reasoning Coverage than GRPO
Yunpeng Ba, Zhi Zheng, Yue Xie +7
Evolution Strategies (ES) have recently emerged as a memory-efficient post-training paradigm for LLM reasoning. However, the optimization behavior of ES remains understudied, makin…
Agentic ESOpt: Fine-Tuning Long-Horizon LLM Agents with Minimal GPU Requirements
Zhi Zheng, Rongsheng Chen, Yunpeng Ba +3
Reinforcement Learning (RL) has been promising in single-turn LLM fine-tuning. However, long-horizon agentic reasoning introduces increasingly branching interactions and sparse rew…
Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging
Yu Gu, Zhi Zheng, Yunpeng Ba +3
Evolution Strategy (ES) is a promising alternative to gradient-based fine-tuning for resource-constrained Large Language Model (LLM) reasoning. However, directly applying ES to bil…
Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees
Fu Luo, Yaoxin Wu, Zhi Zheng +1
Recent neural combinatorial optimization (NCO) methods have shown promising problem-solving ability without requiring domain-specific expertise. Most existing NCO methods use train…
Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design
Zhi Zheng, Zhuoliang Xie, Zhenkun Wang +1
Handcrafting heuristics for solving complex optimization tasks (e.g., route planning and task allocation) is a common practice but requires extensive domain knowledge. Recently, La…
UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems
Zhi Zheng, Changliang Zhou, Tong Xialiang +2
Single-stage neural combinatorial optimization solvers have achieved near-optimal results on various small-scale combinatorial optimization (CO) problems without requiring expert k…
DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems
Zhi Zheng, Shunyu Yao, Zhenkun Wang +3
The min-max vehicle routing problem (min-max VRP) traverses all given customers by assigning several routes and aims to minimize the length of the longest route. Recently, reinforc…