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Problem Decomposition

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Showing 1–25 of 54 papers

TitleStatusHype
MAS-Zero: Designing Multi-Agent Systems with Zero SupervisionCode2
Meta-Design Matters: A Self-Design Multi-Agent SystemCode2
SparseLLM: Towards Global Pruning for Pre-trained Language ModelsCode2
TableTime: Reformulating Time Series Classification as Zero-Shot Table Understanding via Large Language ModelsCode1
SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code GenerationCode1
Divide-or-Conquer? Which Part Should You Distill Your LLM?Code1
Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex ReasoningCode1
Decomposition Strategies and Multi-shot ASP Solving for Job-shop SchedulingCode1
AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System NeedCode0
RAISE: Enhancing Scientific Reasoning in LLMs via Step-by-Step RetrievalCode0
Beyond Accuracy: Dissecting Mathematical Reasoning for LLMs Under Reinforcement Learning—0
Interpretable Traces, Unexpected Outcomes: Investigating the Disconnect in Trace-Based Knowledge Distillation—0
Trace-of-Thought Prompting: Investigating Prompt-Based Knowledge Distillation Through Question Decomposition—0
Training Large Language Models to Reason via EM Policy Gradient—0
Availability of Perfect Decomposition in Statistical Linkage Learning for Unitation-based Function Concatenations—0
LADDER: Self-Improving LLMs Through Recursive Problem Decomposition—0
The working principles of model-based GAs fall within the PAC framework: A mathematical theory of problem decomposition—0
Stackelberg Game Based Performance Optimization in Digital Twin Assisted Federated Learning over NOMA Networks—0
Utilizing ChatGPT in a Data Structures and Algorithms Course: A Teaching Assistant's Perspective—0
Navigating the Nuances: A Fine-grained Evaluation of Vision-Language Navigation—0
Multi-service collaboration and composition of cloud manufacturing customized production based on problem decomposition—0
Context-aware Diversity Enhancement for Neural Multi-Objective Combinatorial Optimization—0
Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective—0
A Composite Decomposition Method for Large-Scale Global Optimization—0
Client Orchestration and Cost-Efficient Joint Optimization for NOMA-Enabled Hierarchical Federated Learning—0
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