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Paper Citation Record · LEDGER

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator

As of 22 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.10960.

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

pith.paper-citation-record.v1
2607.10960 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T08:03:34.460210Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

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

25 of 25 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9a57aea9-3f85-494c-a2a9-acd03bdea77b · outbound

This paper cites Almgren and N.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Almgren and N

Reference 1

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:d339862051525e4896b4d9f175688492c19e5bfa45cec4302584fd44a725ed8c

Observation 2492ff73-816e-4348-93b1-5d95af8e8f8e · outbound

This paper cites Angeris and T.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Angeris and T

Reference 2

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:56257cc88d3cfabf1728c93a5921d62b7cf93fafd49b048c0e5981cf268fbde2

Observation c54da645-bb86-469d-b945-13b6480257cc · outbound

This paper cites Angeris, H.-T.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Angeris, H.-T

Reference 3

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:898b1059cc2dc079e7f9b8fc4e31836c370048f6d0e88793fac7c9fbae5c8950

Observation 29e329f0-e800-43be-9878-5d55ac1b039e · outbound

This paper cites Baggiani, M.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Baggiani, M

Reference 4

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:06179448c2bd92b3e47aa5757ae1bfab8bfa76130ec0ba1d56db9c4f6ed7df22

Observation 127f2370-f7af-4447-bb9d-b0e28d68d5e4 · outbound

This paper cites Optimal Dynamic Fees in Automated Market Makers.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Optimal Dynamic Fees in Automated Market Makers

Reference 5

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:aad1f3994d104a4b17e93e356959d859415a62a59871fa53e3f899c0811b4b22

Observation 686c71c3-81e9-4922-94dc-aac8f41084fe · outbound

This paper cites DEX Specs: A Mean Field Approach to DeFi Currency Exchanges.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator DEX Specs: A Mean Field Approach to DeFi Currency Exchanges

Reference 6

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:6458dceced76d35147b917929f04ee5f0ad8addd2f0f6646341541907480e18a

Observation dc0a8c1d-833e-4136-b4e7-c185e73a0aa2 · outbound

This paper cites Bergault, L.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Bergault, L

Reference 7

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:3df7277e2b7056962630da350a31d2c769dcb6c72d84afd0da1025fc9601038b

Observation 08e92493-af4f-4a1f-9e06-df3d906b51e1 · outbound

This paper cites Bertsimas and A.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Bertsimas and A

Reference 8

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:81cbc88293eb113d631fc1cc0933beeec980b3b85449dbe33f76a91b0a40b5e3

Observation 6cf744d3-af51-44fe-a59e-dc2cf7b527de · outbound

This paper cites Optimal Fees for Liquidity Provision in Automated Market Makers.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Optimal Fees for Liquidity Provision in Automated Market Makers

Reference 9

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:d1f34537f1e9dd92ee460fe6829a9ec0d62c8ab10851e84312197a3e61c4f4f7

Observation 070351b2-1eb1-4064-b694-cbcdc62225e5 · outbound

This paper cites The Adoption of Blockchain-based Decentralized Exchanges.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator The Adoption of Blockchain-based Decentralized Exchanges

Reference 10

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:b39c7a67c014a608d7ea7e09d9d9a38a9dadf9c4fbe02b75eb4cc9b41f803a2d

Observation 7f9db9a8-b911-46d5-9774-691ebd0bc3d4 · outbound

This paper cites Cartea, F.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Cartea, F

Reference 11

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:c2ce10a17f1429a0e54c75a926685d5c1535e92fad9ca939b1cb5bac49024645

Observation cc601262-2912-47ac-8e5b-a92d2b600c6a · outbound

This paper cites Cartea, F.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Cartea, F

Reference 12

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:b8f6fca70cb8e03f5c9dd00ff3161970877e3e96f67da7612d4f670321872888

Observation 7f3843e4-f10b-46b6-9742-65733e0235b5 · outbound

This paper cites Daian, S.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Daian, S

Reference 13

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:54df5c7106319368686cced6ea995e43cef79005343fea7af1934f2e0c009b66

Observation dc4d2559-d529-4eeb-9319-b30586a721c9 · outbound

This paper cites Hasbrouck, T.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Hasbrouck, T

Reference 14

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:fe14ab6021067c3de208ab8921bd475185973f8c82dee5094e93bfc287d7288a

Observation 30d8f3ed-c262-48e1-8026-18fef16878f9 · outbound

This paper cites van Hasselt.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator van Hasselt

Reference 15

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:935485991186682a117a300f9668671f2b2812592f0d6403a7449b1826e6293d

Observation ce380760-c35c-4d24-9bab-a27016fd29f4 · outbound

This paper cites Henderson, R.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Henderson, R

Reference 16

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:ccebcc765fd95e5c90f966f21ec00d12287da927a6fe5b001a8fe1dde28e5dda

Observation 15f036eb-55c2-49e5-8b85-f7f1ec218e40 · outbound

This paper cites Hendricks and D.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Hendricks and D

Reference 17

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:8e2c086fb72792808a92084c4271ddf5a38edc2556a7095585bb2da51ddafcd6

Observation 2eb0b097-f75d-4365-88b3-8c428e9c123b · outbound

This paper cites Lehar and C.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Lehar and C

Reference 18

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:16c7db8f2c1834d1e218ddc67f2553cf54eeca898977f6da234d145fefeee41a

Observation fcb3b09d-0e63-425b-a229-bd2f49770f96 · outbound

This paper cites Automated Market Making and Loss-Versus-Rebalancing.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Automated Market Making and Loss-Versus-Rebalancing

Reference 19

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:ae86ea6bb5f48b94dea172808817d697408fe81803504d1083c5057f7ea0fcde

Observation 6eb17214-9c48-45b0-9479-3888b6c931bf · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Unresolved cited work

Reference 20

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:342c0892cc099c0655d533632b17948d01df0e0ece0e86a27ca202b2737654a3

Observation b78170ed-87cf-4328-8c4b-e93b9d709afd · outbound

This paper cites Nevmyvaka, Y.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Nevmyvaka, Y

Reference 21

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Observation 9a9661cf-9369-447e-8f4d-42ae0053e2ab · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Unresolved cited work

Reference 22

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:1548b9ef23fbb8788f2c976f3368fdf349a0e68af63bcaff1ea79ea5d1cf8751

Observation c61dc13a-24cd-4294-950c-a84ddbf2db22 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Unresolved cited work

Reference 23

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:175a4353c47ecb75f88ae2a30498678ddafe2d3239d87b549b484a38e3157245

Observation 2576acd7-d6e0-49d2-b290-3520c9fde5e3 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Unresolved cited work

Reference 24

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:28b61a4c0e5fca028e5f4eef4f9374eeb1aa1655453291ebbb5f4aca76b3ea06

Observation 8c8f4402-39f8-47d4-99af-1290ada7e274 · outbound

This paper cites Causal Effects of Protocol-Fee Changes on Liquidity Provision in Automated Market Makers.

Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator Causal Effects of Protocol-Fee Changes on Liquidity Provision in Automated Market Makers

Reference 25

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source=pdf_text observed=2026-07-14T08:03:34.460210Z digest=sha256:2025d7e0349e381b9b215284409d612bb11b5f61f3d494c9518ddc01ce06ab69

Pith citing papers

No inbound Pith citation observations are available.