Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T20:29:20.636239Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 100 of 118 outbound references and 1 inbound Pith citation observation for arXiv:2508.10520.
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 2026-08-05T20:29:20.636239Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T04:55:54.373268Z
100 of 118 outbound references displayed
External citation measurements
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Observation 735d4639-15b5-428d-add8-29f5afd41273 · outbound
Nonlocal Monte Carlo via Reinforcement Learning make− break
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Reference 4
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Nonlocal Monte Carlo via Reinforcement Learning RLNMC (to- tal)
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Nonlocal Monte Carlo via Reinforcement Learning 4 we also show the the average energy (number of unsatisfied clauses) for the scale free problems in Fig
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Reference 13
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Nonlocal Monte Carlo via Reinforcement Learning Turing in the shadows of Nobel and Abel: an algorithmic story behind two recent prizes
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Nonlocal Monte Carlo via Reinforcement Learning Kirkpatrick, C
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Nonlocal Monte Carlo via Reinforcement Learning Albash and D
Reference 21
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Reference 22
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Nonlocal Monte Carlo via Reinforcement Learning Wolff, Collective monte carlo updating for spin sys- tems, Phys
Reference 24
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Nonlocal Monte Carlo via Reinforcement Learning Houdayer, A cluster monte carlo algorithm for 2- dimensional spin glasses, The European Physical Jour- nal B - Condensed Matter and Complex Systems 22, 479 (2001)
Reference 25
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Nonlocal Monte Carlo via Reinforcement Learning Hamze and N
Reference 26
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Nonlocal Monte Carlo via Reinforcement Learning Efficient subgraph-based sampling of Ising-type models with frustration
Reference 27
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Nonlocal Monte Carlo via Reinforcement Learning Hen, Solving spin glasses with optimized trees of clus- tered spins, Phys
Reference 29
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Nonlocal Monte Carlo via Reinforcement Learning Nonequilibrium Monte Carlo for unfreezing variables in hard combinatorial optimization
Reference 30
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Nonlocal Monte Carlo via Reinforcement Learning Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon
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Reference 34
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Nonlocal Monte Carlo via Reinforcement Learning Neural Combinatorial Optimization with Reinforcement Learning
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Nonlocal Monte Carlo via Reinforcement Learning Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
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Reference 37
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Nonlocal Monte Carlo via Reinforcement Learning Attention, Learn to Solve Routing Problems!
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Observation 94b82968-44c6-467c-a346-71aedc998b1d · outbound
Nonlocal Monte Carlo via Reinforcement Learning Learning Combinatorial Optimization Algorithms over Graphs
Reference 39
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Nonlocal Monte Carlo via Reinforcement Learning Exploratory Combinatorial Optimization with Reinforcement Learning
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Nonlocal Monte Carlo via Reinforcement Learning T¨ onshoff, B
Reference 42
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Nonlocal Monte Carlo via Reinforcement Learning Mazyavkina, S
Reference 43
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Nonlocal Monte Carlo via Reinforcement Learning Learning What to Defer for Maximum Independent Sets
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Nonlocal Monte Carlo via Reinforcement Learning What's Wrong with Deep Learning in Tree Search for Combinatorial Optimization
Reference 47
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Nonlocal Monte Carlo via Reinforcement Learning Perdomo-Ortiz, A
Reference 50
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Nonlocal Monte Carlo via Reinforcement Learning Valiante, M
Reference 51
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Nonlocal Monte Carlo via Reinforcement Learning Dobrynin, A
Reference 52
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Nonlocal Monte Carlo via Reinforcement Learning Dobrynin, M
Reference 53
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Nonlocal Monte Carlo via Reinforcement Learning Heydaribeni, X
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Nonlocal Monte Carlo via Reinforcement Learning Boettcher, Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture, Nature Communications 14, 5658 (2023)
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Reference 96
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Observation 8682f84b-1543-4a2c-8609-2909ec82fbbb · outbound
Nonlocal Monte Carlo via Reinforcement Learning Chowdhury, A
Reference 98
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 9f130535-f850-4717-9449-e3b4627d779f · outbound
Nonlocal Monte Carlo via Reinforcement Learning Unresolved cited work
Reference 99
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation a2687877-93ff-4ea1-b4d3-be112d951401 · outbound
Nonlocal Monte Carlo via Reinforcement Learning Chowdhury, N
Reference 100
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dcbfa5b8-e556-4bb2-ac80-961514b8a75f · outbound
Nonlocal Monte Carlo via Reinforcement Learning How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits
Reference 101
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1c581231-745a-4bf0-854d-8300b85a0432 · inbound
Demonstrating Real Advantage of Machine-Learning-Enhanced Monte Carlo for Combinatorial Optimization Nonlocal Monte Carlo via Reinforcement Learning
Reference 46
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.