Problem Decomposition

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

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Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

19 shown of 19 papers with code (54 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• SparseLLM: Towards Global Pruning for Pre-trained Language Models
  28 Feb 2024 2 repositories listed Syntology ran 3 of 9 samples · 6 unverified
  The transformative impact of large language models (LLMs) like LLaMA and GPT on natural language processing is countered by their prohibitive computational demands.
• AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need
  18 Jun 2025 1 repository listed
  Large language model based multi-agent systems have demonstrated significant potential in social simulation and complex task resolution domains.
• RAISE: Enhancing Scientific Reasoning in LLMs via Step-by-Step Retrieval
  10 Jun 2025 1 repository listed
  We analyze that unlike other baselines, RAISE retrieves documents that are not only similar in terms of the domain knowledge, but also documents logically more relevant.
• MAS-Zero: Designing Multi-Agent Systems with Zero Supervision
  26 May 2025 1 repository listed
  Multi-agent systems (MAS) leveraging the impressive capabilities of Large Language Models (LLMs) hold significant potential for tackling complex tasks.
• Meta-Design Matters: A Self-Design Multi-Agent System
  21 May 2025 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  These manual designs often fail to align with the underlying LLMs' strengths and struggle to adapt to novel tasks.
• TableTime: Reformulating Time Series Classification as Zero-Shot Table Understanding via Large Language Models
  24 Nov 2024 1 repository listed
  Despite their effectiveness, we reveal that these methods conceal three inherent bottlenecks: (1) they struggle to encode temporal and channel-specific information in a lossless manner, both of which are critical…
• SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation
  17 Nov 2024 1 repository listed
  Large language models demonstrate exceptional performance in simple code generation tasks but still face challenges in tackling complex problems.
• Divide-or-Conquer? Which Part Should You Distill Your LLM?
  22 Feb 2024 1 repository listed Syntology ran 9 of 11 samples · 2 unverified · 11 pointer-only (licence)
  Recent methods have demonstrated that Large Language Models (LLMs) can solve reasoning tasks better when they are encouraged to solve subtasks of the main task first.
• Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoning
  21 Oct 2023 1 repository listed Syntology ran 5 of 7 samples · 2 unverified · 7 pointer-only (licence)
  Additionally, we show that DaSLaM is not limited by the solver's capabilities as a function of scale; e.
• Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model Reasoning
  1 Oct 2023 1 repository listed Syntology ran 4 of 11 samples · 7 unverified · 11 pointer-only (licence)
  These methods employ consistent models, sample sizes, prompting methods and levels of problem decomposition, regardless of the problem complexity.
• Fast Matrix Multiplication Without Tears: A Constraint Programming Approach
  1 Jun 2023 1 repository listed
  In this work, we propose a simple yet novel Constraint Programming approach to find non-commutative algorithms for fast matrix multiplication or provide proof of infeasibility otherwise.
• Rolling Horizon based Temporal Decomposition for the Offline Pickup and Delivery Problem with Time Windows
  6 Mar 2023 1 repository listed
  In smaller problem instances, the baseline approach is as competitive as our framework.
• Comparison of Model-Free and Model-Based Learning-Informed Planning for PointGoal Navigation
  17 Dec 2022 1 repository listed
  In this work, we compare the state-of-the-art Deep Reinforcement Learning based approaches with Partially Observable Markov Decision Process (POMDP) formulation of the point goal navigation problem.
• Distilling Reasoning Capabilities into Smaller Language Models
  1 Dec 2022 1 repository listed
  In this work, we propose an alternative reasoning scheme, Socratic CoT, that learns a decomposition of the original problem into a sequence of subproblems and uses it to guide the intermediate reasoning steps.
• Decomposition Strategies and Multi-shot ASP Solving for Job-shop Scheduling
  16 May 2022 1 repository listed
  We devise and investigate a variety of decomposition strategies in terms of the number and size of time windows as well as heuristics for choosing their operations.
• Fast reinforcement learning with generalized policy updates
  9 Jul 2020 1 repository listed
  Both strategies considerably reduce the amount of data needed to solve a reinforcement-learning problem.
• Learning Reward Machines for Partially Observable Reinforcement Learning
  1 Dec 2019 1 repository listed
  Reward Machines (RMs), originally proposed for specifying problems in Reinforcement Learning (RL), provide a structured, automata-based representation of a reward function that allows an agent to decompose problems into…
• Decomposition Methods with Deep Corrections for Reinforcement Learning
  6 Feb 2018 1 repository listed
  In contexts where an agent interacts with multiple entities, utility decomposition can be used to separate the global objective into local tasks considering each individual entity independently.
• Meta-Optimizing Semantic Evolutionary Search
  11 Jul 2017 1 repository listed
  I present MOSES (meta-optimizing semantic evolutionary search), a new probabilistic modeling (estimation of distribution) approach to program evolution.

Syntology lines on 5 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.