Paper Citation Record · LEDGER

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing

As of 11 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2501.19102.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.19102 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:21:34.269304Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

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verified fuzzy17
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 46685658-42f3-4a0c-b232-ef492f9898a4 · outbound

This paper cites Laser-based manufacturing concepts for efficient production of tailor welded sheet metals,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Laser-based manufacturing concepts for efficient production of tailor welded sheet metals,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.791442Z

Source-reported events for the cited work

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Observation 0f4785f2-db45-4194-b7eb-91e8fbb583ca · outbound

This paper cites Laser powder bed fusion of 316l stainless steel: Industrial relevance and process optimization,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Laser powder bed fusion of 316l stainless steel: Industrial relevance and process optimization,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.761079Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fe119aa8-4450-4e5f-81bf-d7fa9dd63f02 · outbound

This paper cites A review on laser processing in electronic and mems packaging,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing A review on laser processing in electronic and mems packaging,

Reference 3

Resolution: verified exact; doi, observed 2026-08-09T21:21:34.399121Z

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Observation 70cedd7e-cf48-4006-8bc3-4d0912f88864 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Unresolved cited work

Reference 4

Resolution: verified exact; doi, observed 2026-08-09T21:21:34.383290Z

Source-reported events for the cited work

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Observation 24b6b3f7-bbf1-4282-a972-ce415d17b569 · outbound

This paper cites Fault-tolerant laser welding in automotive industries,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Fault-tolerant laser welding in automotive industries,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.745998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 931b33f2-6b45-475d-bab0-de18ee1dc252 · outbound

This paper cites Deep reinforcement learn- ing for robotic manipulation with asynchronous off-policy updates,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Deep reinforcement learn- ing for robotic manipulation with asynchronous off-policy updates,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T21:21:34.143665Z

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Observation 8281d51f-de51-44e5-a2ed-fc077baeed69 · outbound

This paper cites Magnetic control of tokamak plasmas through deep reinforcement learning,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Magnetic control of tokamak plasmas through deep reinforcement learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.720672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 81838b56-9215-4716-a719-36f2f5572eb9 · outbound

This paper cites Adaptive laser welding control: A reinforcement learning approach,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Adaptive laser welding control: A reinforcement learning approach,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.704764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0af85a80-f666-4e40-a4ed-f6fb95f53181 · outbound

This paper cites Reinforcement learning for laser welding speed control minimizing bead width error,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Reinforcement learning for laser welding speed control minimizing bead width error,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.687687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 90f141b4-888c-4f41-b6ae-3137c6cbdb5a · outbound

This paper cites In- telligent laser welding through representation, prediction, and control learning: An architecture with deep neural networks and reinforcement learning,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing In- telligent laser welding through representation, prediction, and control learning: An architecture with deep neural networks and reinforcement learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.672757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 98bd7eb2-9e48-413f-8708-154bba45267a · outbound

This paper cites Development of a defect-detection platform using photodiode signals collected from the melt pool of laser powder-bed fusion,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Development of a defect-detection platform using photodiode signals collected from the melt pool of laser powder-bed fusion,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.657300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 264887d3-8c1a-48e4-a7e4-0e83f07f1699 · outbound

This paper cites Steel corrosion behaviour in acidic solution for application in petrochemical distillation systems,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Steel corrosion behaviour in acidic solution for application in petrochemical distillation systems,

Reference 12

Resolution: verified exact; doi, observed 2026-08-09T21:21:34.366346Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 717a2347-c5f0-4a3c-937f-67bb7fa34044 · outbound

This paper cites Anti-fouling surface modified stainless steel for food processing,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Anti-fouling surface modified stainless steel for food processing,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.641189Z

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Observation dbbfebc0-c96c-43ad-a31a-4e67e3919048 · outbound

This paper cites Electrophoretic deposition of natural hydroxyapatite on medical grade 316l stainless steel,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Electrophoretic deposition of natural hydroxyapatite on medical grade 316l stainless steel,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.625005Z

Source-reported events for the cited work

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Observation b6d51ca8-230b-4445-b159-2cf31c4273e9 · outbound

This paper cites Laser beam welding of 316l t-joint: microstructure, microhardness, distortion, and residual stress,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Laser beam welding of 316l t-joint: microstructure, microhardness, distortion, and residual stress,

Reference 15

Resolution: verified exact; doi, observed 2026-08-09T21:21:34.351040Z

Source-reported events for the cited work

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Observation 9c38edca-37d5-4c7e-9887-f52a3862f734 · outbound

This paper cites Xilinx/brevitas,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Xilinx/brevitas,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T21:21:34.190366Z

Source-reported events for the cited work

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Observation 59895f30-0c17-4b9d-b37f-e7fc945f2519 · outbound

This paper cites Reinforcement learning: An introduction,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Reinforcement learning: An introduction,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T21:21:34.195128Z

Source-reported events for the cited work

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Observation eba56c19-3e81-4eec-9369-fbff910ae8e5 · outbound

This paper cites Unpack- ing reward shaping: Understanding the benefits of reward engineering on sample complexity,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Unpack- ing reward shaping: Understanding the benefits of reward engineering on sample complexity,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.596966Z

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Observation 380a74c1-72a3-4312-bcbb-6cc58ba144c5 · outbound

This paper cites Absorbance measurement for in situ process regime identification in laser processing,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Absorbance measurement for in situ process regime identification in laser processing,

Reference 19

Resolution: verified exact; doi, observed 2026-08-09T21:21:34.324228Z

Source-reported events for the cited work

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Observation 3ccfe65c-11eb-41a6-bc89-25c2e2e24425 · outbound

This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T21:21:34.209926Z

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Observation ee86fb01-b651-4aba-8042-b18604bea045 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Soft Actor-Critic Algorithms and Applications

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T21:21:34.215312Z

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Observation 4a14fb0d-c3b4-4b8a-b61e-430707e62963 · outbound

This paper cites Maximum Entropy RL (Provably) Solves Some Robust RL Problems.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Maximum Entropy RL (Provably) Solves Some Robust RL Problems

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T21:21:34.220265Z

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Observation aa2e1a24-51cc-43a6-894d-9df2f0be3928 · outbound

This paper cites [Online].

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing [Online]

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.569756Z

Source-reported events for the cited work

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Observation 57097f61-9eaa-43b8-8c27-f1b11949d11d · outbound

This paper cites Auto-Encoding Variational Bayes.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Auto-Encoding Variational Bayes

Reference 24

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Observation 2610936a-af4c-4314-891d-3e85f610f5b9 · outbound

This paper cites Keyhole fluctuation and pore formation mechanisms during laser powder bed fusion additive manufacturing,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Keyhole fluctuation and pore formation mechanisms during laser powder bed fusion additive manufacturing,

Reference 25

Resolution: malformed identifier; raw_fallback, observed 2026-08-09T21:21:34.553370Z

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Observation 495625f8-ab92-48d6-984a-98a8371c83e0 · outbound

This paper cites A review on melt-pool characteristics in laser welding of metals,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing A review on melt-pool characteristics in laser welding of metals,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.535559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3b8c5ce7-042f-4650-8015-088c42342341 · outbound

This paper cites Control of meltpool shape in laser welding,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Control of meltpool shape in laser welding,

Reference 27

Resolution: verified exact; doi, observed 2026-08-09T21:21:34.308189Z

Source-reported events for the cited work

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Observation 3729f8ef-6d40-42a7-910e-4a29e5e949db · outbound

This paper cites Defectometry, distortion analysis and metallurgical properties in the keyhole and conduction mode of laser beam welding of al–mg–sc alloy butt joints,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Defectometry, distortion analysis and metallurgical properties in the keyhole and conduction mode of laser beam welding of al–mg–sc alloy butt joints,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.505147Z

Source-reported events for the cited work

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Observation bd3fd8fa-da94-487e-a89d-719a374b7b5e · outbound

This paper cites Effect of laser beam welding on microstructure, tensile strength and fatigue behaviour of duplex stainless steel 2205,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Effect of laser beam welding on microstructure, tensile strength and fatigue behaviour of duplex stainless steel 2205,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.489313Z

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Observation ced8539d-3452-46d4-a294-28210d944902 · outbound

This paper cites Reinforcement learning with perceptual aliasing: The perceptual distinctions approach,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Reinforcement learning with perceptual aliasing: The perceptual distinctions approach,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.473293Z

Source-reported events for the cited work

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Observation f4bf6f0e-42cb-49e0-80c6-13b9156b7f57 · outbound

This paper cites Domain randomization for transferring deep neural networks from simulation to the real world,.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Domain randomization for transferring deep neural networks from simulation to the real world,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T21:21:34.269304Z

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Observation 09f7c8c1-477c-4ca2-9772-381269c2f5fe · outbound

This paper cites Available: https://link.springer.com/article/10.1007/ s40436-014-0088-8.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Available: https://link.springer.com/article/10.1007/ s40436-014-0088-8

Reference 2014

Resolution: malformed identifier; raw_fallback, observed 2026-08-09T21:21:34.776549Z

Source-reported events for the cited work

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Observation 587e0402-cd24-494c-bd5d-465a31d2cffa · outbound

This paper cites Available: https://onlinelibrary.wiley.com/doi/abs/10.

Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing Available: https://onlinelibrary.wiley.com/doi/abs/10

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:21:34.520311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

No inbound Pith citation observations are available.