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20232026
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6 papers · 1 filter

cs.LG2026

GeoNest: Learning to Select Failure-Aware Neighborhoods for the Irregular Knapsack Problem in a Circular Container

Zhongman Du, Huiming Zhang, Linlin Yang +2

The two-dimensional irregular knapsack problem in a fixed circular container is an important combinatorial optimization problem for maximizing material utilization in manufacturing…

cs.LG2026

GraphHCA: Closed-Form Hindsight Credit Assignment for Long-Horizon LLM Agents

Haodong Zhu, Yangyang Ren, Changbai Li +4

Group-based reinforcement learning (RL) has advanced large language models (LLMs) and is increasingly extending to agentic tasks, where sparse terminal rewards make step-level cred…

cs.LG2026

Cross-Rollout Bellman Closure for Long-Horizon Agentic Reinforcement Learning

Yangyang Ren, Haodong Zhu, Linlin Yang +3

Group-based reinforcement learning such as GRPO trains LLM agents by comparing rollouts sampled for each task, without a learned critic. In long-horizon settings, these rollouts re…

cs.LG2026

Kalman Meets Curriculum: Efficient Dynamic Prompt Selection for Adaptive RL Finetuning

Haodong Zhu, Yangyang Ren, Yanjing Li +4

Reinforcement learning (RL) finetuning significantly enhances the reasoning capabilities of large language models (LLMs), yet its effectiveness critically depends on selecting prom…

cs.LG2026

FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models

Haoyu Huang, Linlin Yang, Sheng Xu +5

Diffusion Large Language Models (dLLMs) refine tokens iteratively but commit them irreversibly, leading to a "stability lag" where early decisions remain fragile even after being w…

cs.LG2026

Unbiased Dynamic Pruning for Efficient Group-Based Policy Optimization

Haodong Zhu, Yangyang Ren, Yanjing Li +6

Group Relative Policy Optimization (GRPO) effectively scales LLM reasoning but incurs prohibitive computational costs due to its extensive group-based sampling requirement. While r…