Copertina

Chain-of-Context Learning: Dynamic Constraint Understanding for Multi-Task VRPs

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Gui, Shuangchun, Liu, Suyu, Wang, Xuehe, Cao, Zhiguang
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

ARC: Leveraging Compositional Representations for Cross-Problem Learning on VRPs
di: Jeong, Han-Seul, et al.
Pubblicazione: (2025)

Degree of Staleness-Aware Data Updating in Federated Learning
di: Liu, Tao, et al.
Pubblicazione: (2025)

Understanding the Dynamics of Demonstration Conflict in In-Context Learning
di: Jiao, Difan, et al.
Pubblicazione: (2026)

Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts under State-Decomposable MDP
di: Pan, Yuxin, et al.
Pubblicazione: (2025)

Learning to Handle Complex Constraints for Vehicle Routing Problems
di: Bi, Jieyi, et al.
Pubblicazione: (2024)

Hybrid-Balance GFlowNet for Solving Vehicle Routing Problems
di: Zhang, Ni, et al.
Pubblicazione: (2025)

MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
di: Zhou, Jianan, et al.
Pubblicazione: (2024)

LC-Eval: A Bilingual Multi-Task Evaluation Benchmark for Long-Context Understanding
di: Jubair, Sheikh, et al.
Pubblicazione: (2025)

Soft Conflict-Resolution Decision Transformer for Offline Multi-Task Reinforcement Learning
di: Wang, Shudong, et al.
Pubblicazione: (2025)

RADAR: Learning to Route with Asymmetry-aware DistAnce Representations
di: Yi, Hang, et al.
Pubblicazione: (2026)

Hierarchical Learning-based Graph Partition for Large-scale Vehicle Routing Problems
di: Pan, Yuxin, et al.
Pubblicazione: (2025)

Multi-Task Learning with Multi-Task Optimization
di: Bai, Lu, et al.
Pubblicazione: (2024)

CASTER: Breaking the Cost-Performance Barrier in Multi-Agent Orchestration via Context-Aware Strategy for Task Efficient Routing
di: Liu, Shanyv, et al.
Pubblicazione: (2026)

Chain-of-Restoration: Multi-Task Image Restoration Models are Zero-Shot Step-by-Step Universal Image Restorers
di: Cao, Jin, et al.
Pubblicazione: (2024)

Not All Tasks Are Equally Difficult: Multi-Task Deep Reinforcement Learning with Dynamic Depth Routing
di: He, Jinmin, et al.
Pubblicazione: (2023)

Nested Graph Pseudo-Label Refinement for Noisy Label Domain Adaptation Learning
di: Wang, Yingxu, et al.
Pubblicazione: (2025)

Beyond ESG Scores: Learning Dynamic Constraints for Sequential Portfolio Optimization
di: Li, Xin, et al.
Pubblicazione: (2026)

SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy
di: Goh, Yong Liang, et al.
Pubblicazione: (2025)

Harmonizing Real-Time Constraints and Long-Horizon Reasoning: An Asynchronous Agentic Framework for Dynamic Scheduling
di: Cao, Shijie, et al.
Pubblicazione: (2026)

VAGPO: Vision-augmented Asymmetric Group Preference Optimization for Graph Routing Problems
di: Liu, Shiyan, et al.
Pubblicazione: (2025)

How Transformers Learn In-Context Recall Tasks? Optimality, Training Dynamics and Generalization
di: Nguyen, Quan, et al.
Pubblicazione: (2025)

FocusLLM: Precise Understanding of Long Context by Dynamic Condensing
di: Li, Zhenyu, et al.
Pubblicazione: (2024)

Learning Memory-Enhanced Improvement Heuristics for Flexible Job Shop Scheduling
di: Wang, Jiaqi, et al.
Pubblicazione: (2026)

Lost in Tokenization: Context as the Key to Unlocking Biomolecular Understanding in Scientific LLMs
di: Zhuang, Kai, et al.
Pubblicazione: (2025)

MMLU-Reason: Benchmarking Multi-Task Multi-modal Language Understanding and Reasoning
di: Tie, Guiyao, et al.
Pubblicazione: (2025)

UniMo: Unified Motion Generation and Understanding with Chain of Thought
di: Wang, Guocun, et al.
Pubblicazione: (2026)

Mimic In-Context Learning for Multimodal Tasks
di: Jiang, Yuchu, et al.
Pubblicazione: (2025)

Aligning Paralinguistic Understanding and Generation in Speech LLMs via Multi-Task Reinforcement Learning
di: Chen, Jingxiang, et al.
Pubblicazione: (2026)

Understanding and Enforcing Weight Disentanglement in Task Arithmetic
di: Liu, Shangge, et al.
Pubblicazione: (2026)

Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
di: Zhang, Cong, et al.
Pubblicazione: (2022)

Advancing Graph Few-Shot Learning via In-Context Learning
di: Guan, Renchu, et al.
Pubblicazione: (2026)

Identifying Semantic Induction Heads to Understand In-Context Learning
di: Ren, Jie, et al.
Pubblicazione: (2024)

Learning Agent-Compatible Context Management for Long-Horizon Tasks
di: Yi, Lu, et al.
Pubblicazione: (2026)

Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
di: Zhang, Cong, et al.
Pubblicazione: (2024)

Task-Agnostic Learning to Accomplish New Tasks
di: Zhang, Xianqi, et al.
Pubblicazione: (2022)

GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time
di: Ye, Haoran, et al.
Pubblicazione: (2023)

Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
di: Bi, Jieyi, et al.
Pubblicazione: (2026)

SupChain-Bench: Benchmarking Large Language Models for Real-World Supply Chain Management
di: Guan, Shengyue, et al.
Pubblicazione: (2026)

Cross-Problem Learning for Solving Vehicle Routing Problems
di: Lin, Zhuoyi, et al.
Pubblicazione: (2024)

DRAFT-RL: Multi-Agent Chain-of-Draft Reasoning for Reinforcement Learning-Enhanced LLMs
di: Li, Yuanhao, et al.
Pubblicazione: (2025)