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