Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T10:38:06.366136Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 1 inbound Pith citation observation for arXiv:2502.02941.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T10:38:06.366136Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-08T11:46:42.010486Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T19:31:08.850812Z
73 of 73 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 6ba09ec5-727d-427e-a6c6-e3f39e47a24b · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Machine learning for combinatorial optimization: a methodological tour d’horizon,
Reference 1
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Attention, Learn to Solve Routing Problems!
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Observation b9d8df75-e059-49d7-b0f3-d50f384c1503 · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
Reference 3
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Pomo: Policy optimization with multiple optima for reinforcement learning,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems
Reference 6
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization DIFUSCO: Graph-based diffusion solvers for combinatorial optimization,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization T2t: From distribution learning in training to gradient search in testing for combinatorial optimization,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Unsupervised learning for solving the travelling salesman problem,
Reference 9
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Pointer networks,
Reference 10
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Observation 0b1a54cc-576c-4934-a75e-f03b4a4aa35e · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Graph neural network guided local search for the traveling salesperson problem,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Generalize a small pre-trained model to arbitrarily large tsp instances,
Reference 12
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Observation b6797448-34d9-482d-9a70-60b28d1055a3 · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Neural combinatorial optimization with heavy decoder: Toward large scale generalization,
Reference 13
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Neural Combinatorial Optimization with Reinforcement Learning
Reference 14
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Observation 98f3efb6-f734-4974-bbaf-d1adefcb8502 · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Efficient Active Search for Combinatorial Optimization Problems
Reference 15
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Observation 8d81523e-c279-4c4f-b193-3f4984c55080 · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Consistency Models
Reference 16
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Observation 3e0d1712-d792-4251-9a99-59b6e42b9144 · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Deep unsupervised learning using nonequilibrium thermodynamics,
Reference 17
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Observation 6d0d68f0-6679-4e47-899d-6306b7bc4a81 · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Structured denoising diffusion models in discrete state-spaces,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Argmax flows and multinomial diffusion: Learning categorical distributions,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Learning combinatorial optimization algorithms over graphs,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Learning a latent search space for routing problems using variational autoencoders,
Reference 21
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Reference 22
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Learning plaintext-ciphertext crypto- graphic problems via anf-based sat instance representation,
Reference 23
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Learning 2-opt heuristics for the traveling salesman problem via deep reinforcement learning,
Reference 24
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Learning improvement heuristics for solving routing problems,
Reference 25
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Learning to perform local rewriting for combinatorial optimization,
Reference 26
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Observation d4b4b91b-88d1-414f-aabd-30bf4acd78d1 · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Learning to delegate for large-scale vehicle routing,
Reference 27
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Observation 6cdfaa74-d3f8-4692-b129-9c349a40704b · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Generalize learned heuristics to solve large- scale vehicle routing problems in real-time,
Reference 28
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Observation 0db7e847-6675-4caa-84f1-c94bc9d7f55b · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization The policy-gradient placement and generative routing neural networks for chip design,
Reference 29
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Hubrouter: Learning global routing via hub generation and pin-hub connection,
Reference 30
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets
Reference 31
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Generative modeling by estimating gradients of the data distribution,
Reference 32
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Observation 78dd55b9-cfcc-4498-aad2-3c391ef5d4ed · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Denoising diffusion probabilistic models,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Denoising Diffusion Implicit Models
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Improved techniques for training score-based generative models,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Improved denoising diffusion probabilistic models,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Diffusion models beat gans on image synthesis,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Score-Based Generative Modeling through Stochastic Differential Equations
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Erdos goes neural: an unsupervised learning framework for combinatorial optimization on graphs,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Unsupervised learning for combinatorial opti- mization with principled objective relaxation,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization A tutorial on energy-based learning,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Diffusion models as plug-and-play priors
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization An effective heuristic algorithm for the traveling-salesman problem,
Reference 43
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Concorde tsp solver,
Reference 44
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization The Transformer Network for the Traveling Salesman Problem
Reference 47
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning
Reference 48
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Reference 49
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Combinatorial optimization with graph convolutional networks and guided tree search,
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization What's Wrong with Deep Learning in Tree Search for Combinatorial Optimization
Reference 53
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
Reference 56
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Reference 60
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization 5, and there are no additional theorems needed to be proved
Reference 61
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Reference 62
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Reference 64
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Reference 68
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Reference 69
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Reference 70
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Our source code will be released upon the acceptance of the paper with comprehensive documents
Reference 71
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Observation 2d2eaf72-d26f-4a84-b693-a1334556d222 · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects
Reference 72
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Observation e063a180-2dbc-436f-bd8b-b5f3a78c4f40 · outbound
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects
Reference 73
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Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization Available: https://openreview.net/forum?id=ar92oEosBIg
Reference 2022
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GCCM: Enhancing Generative Graph Prediction via Contrastive Consistency Model Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization
Reference 34
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