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Problem Decomposition
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
RAISE: Enhancing Scientific Reasoning in LLMs via Step-by-Step Retrieval
Beyond Accuracy: Dissecting Mathematical Reasoning for LLMs Under Reinforcement Learning
Meta-Design Matters: A Self-Design Multi-Agent System
Interpretable Traces, Unexpected Outcomes: Investigating the Disconnect in Trace-Based Knowledge Distillation
Trace-of-Thought Prompting: Investigating Prompt-Based Knowledge Distillation Through Question Decomposition
Training Large Language Models to Reason via EM Policy Gradient
Availability of Perfect Decomposition in Statistical Linkage Learning for Unitation-based Function Concatenations
LADDER: Self-Improving LLMs Through Recursive Problem Decomposition
The working principles of model-based GAs fall within the PAC framework: A mathematical theory of problem decomposition
Stackelberg Game Based Performance Optimization in Digital Twin Assisted Federated Learning over NOMA Networks
TableTime: Reformulating Time Series Classification as Zero-Shot Table Understanding via Large Language Models
SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation
Utilizing ChatGPT in a Data Structures and Algorithms Course: A Teaching Assistant's Perspective
Navigating the Nuances: A Fine-grained Evaluation of Vision-Language Navigation
Multi-service collaboration and composition of cloud manufacturing customized production based on problem decomposition
Context-aware Diversity Enhancement for Neural Multi-Objective Combinatorial Optimization
Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective
A Composite Decomposition Method for Large-Scale Global Optimization
SparseLLM: Towards Global Pruning for Pre-trained Language Models
Divide-or-Conquer? Which Part Should You Distill Your LLM?
Client Orchestration and Cost-Efficient Joint Optimization for NOMA-Enabled Hierarchical Federated Learning
Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoning
Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model Reasoning
LLM Guided Inductive Inference for Solving Compositional Problems
Data-driven Topology and Parameter Identification in Distribution Systems with limited Measurements
Fast Matrix Multiplication Without Tears: A Constraint Programming Approach
Rolling Horizon based Temporal Decomposition for the Offline Pickup and Delivery Problem with Time Windows
Comparison of Model-Free and Model-Based Learning-Informed Planning for PointGoal Navigation
Distilling Reasoning Capabilities into Smaller Language Models
Hybridization of evolutionary algorithm and deep reinforcement learning for multi-objective orienteering optimization
Incremental Recursive Ranking Grouping for Large Scale Global Optimization
Distributed Optimization in Distribution Systems with Grid-Forming and Grid-Supporting Inverters
Decomposition Strategies and Multi-shot ASP Solving for Job-shop Scheduling
Dynamic Diagnosis of the Progress and Shortcomings of Student Learning using Machine Learning based on Cognitive, Social, and Emotional Features
Physics-Guided Problem Decomposition for Scaling Deep Learning of High-dimensional Eigen-Solvers: The Case of Schrödinger's Equation
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