NeurIPS 2025 Past Other
Workshop on Differentiable Learning of Combinatorial Algorithms
DiffCoAlg 2025
- Submission deadline
- Sep 6, 2025, 23:59 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (37)
Fetched from OpenReview (v2) on 2026-06-10.
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Accelerating Vehicle Routing via AI-Initialized Genetic Algorithms
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ACCORD: Autoregressive Constraint-satisfying Generation for COmbinatorial Optimization with Routing and Dynamic attention
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Advancing Differentiable Mechanism Design: Neural Architectures for Combinatorial Auctions
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Adversarially-Guided TD: Learning Robust Value Functions with Counter-Example Replay
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ARC: Leveraging Compositional Representations for Cross-Problem Learning on VRPs
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Combinatorial Representations for Temporal Reasoning
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Filter Equivariant Functions: A symmetric account of length-general extrapolation on lists
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Forge: Foundational Optimization Representations from Graph Embeddings
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Fundamental Limits of Local Graph Neural Networks on High-Girth Graphs
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Fuzzy Logic Composition of Diffusion Models
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G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning
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Generalizable Heuristic Generation Through Large Language Models with Meta-Optimization
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How Do Transformers Align Tokens?
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Learning from Algorithm Feedback: One-Shot SAT Solver Guidance with GNNs
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Learning to Handle Constraints in Routing Problems via a Construct-and-Refine Framework
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Learning to Optimize for Mixed-Integer Non-linear Programming with Feasibility Guarantees
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Learning to optimize linear regression tasks with improved distribution-dependent guarantees
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Learning with Local Search MCMC Layers
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Local Fragments, Global Gains: Subgraph Counting using Graph Neural Networks
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LPMARL: Linear Programming-based Task Assignment for Hierarchical Multi-agent Reinforcement Learning
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ML-Guided Primal Heuristics for Mixed Binary Quadratic Programs
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Neural Embedded Mixed-Integer Optimization for Location-Routing Problems
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Offline Decision Transformers for Neural Combinatorial Optimization: Surpassing Heuristics on the Traveling Salesman Problem
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On the benefits of label preserving augmentations for self-supervised SAT solvers
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OptiHive: Ensemble Selection for Learning-Based Optimization via Statistical Modeling
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Optimizing the Dynamic Drone-Assisted Pickup and Delivery Problem with Deep Reinforcement Learning
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Preference-Based Gradient Estimation for ML-Guided Approximate Combinatorial Optimization
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Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation
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Probabilistic Loss Functions for Self-Supervised SAT Solvers
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Reinforcement Learning Assisted Dynamic Large Scale Graph Learning
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RRNCO: Towards Real-World Routing with Neural Combinatorial Optimization
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Scaling Laws for Neural Combinatorial Optimization with LLaMA Models
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Solving Traveling Salesman Problems Using Parallel Environments in Reinforcement Learning
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Structure As Search: Unsupervised Permutation Learning for Combinatorial Optimization
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Test-Time Search in Neural Graph Coarsening for the Capacitated Vehicle Routing Problem
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Towards distillation guarantees under algorithmic alignment
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Unsupervised Learning of Local Updates for Maximum Independent Set in Dynamic Graphs