Paper Citation Record · LEDGER

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making

As of 17 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2505.13580.

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

pith.paper-citation-record.v1
2505.13580 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:23:51.839061Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T04:01:47.660117Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

verified exact1
verified fuzzy17
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 804ec845-de20-4e93-9b4d-6d26ded6b162 · outbound

This paper cites an unresolved cited work.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:23:52.784637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 126dee83-562e-41cc-a021-dc3826e693a1 · outbound

This paper cites Understanding intermediate layers using linear classifier probes.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Understanding intermediate layers using linear classifier probes

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.010219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8de5adb-c0e3-4c68-be17-eef2f830df11 · outbound

This paper cites an unresolved cited work.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:23:52.314488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 10100d75-5239-492a-a95a-67a4ff56b448 · outbound

This paper cites following the sampling rules previously described.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making following the sampling rules previously described

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.443800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 18e5abe6-5693-46f8-87b6-b08c8561b1bb · outbound

This paper cites RvS: What is Essential for Offline RL via Supervised Learning?.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making RvS: What is Essential for Offline RL via Supervised Learning?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.177242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8418f4d-c12e-448f-a473-750e151a3d12 · outbound

This paper cites Scaling Laws for Neural Language Models.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Scaling Laws for Neural Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.254742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ba945f6-d61f-495d-80d7-7f94b25931fe · outbound

This paper cites Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.266031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb4a7052-ec75-495b-8675-9f924b161922 · outbound

This paper cites An Explanation of In-context Learning as Implicit Bayesian Inference.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making An Explanation of In-context Learning as Implicit Bayesian Inference

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.418590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 336de0f0-ba9e-4d7e-bf1f-5a1facb07b33 · outbound

This paper cites Closing the gap: A learning algorithm for lost-sales inventory systems with lead times.Management Science, 66(5):1962–1980,.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Closing the gap: A learning algorithm for lost-sales inventory systems with lead times.Management Science, 66(5):1962–1980,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:53.144498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5c074895-ccab-496c-b162-66b2f0a622a5 · outbound

This paper cites What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.527216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 555a3a58-1ad4-4b1e-8e0d-5d0f968a4a79 · outbound

This paper cites A Survey of Large Language Models.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making A Survey of Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.532451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cca0143d-b1b7-4e81-8286-a71b8bf93069 · outbound

This paper cites label type.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making label type

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:53.063339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4fe58246-b584-43d8-962d-dc2854e5a89b · outbound

This paper cites informing.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making informing

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:53.046301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dbef3af6-8718-4b24-b93e-79d5ad6f6cf0 · outbound

This paper cites 39 • GPTmodelarchitecture: Duetothedifferentdatagenerationmethodsandthespecialstructure of the underlying problems, we employ a different GPT architecture.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making 39 • GPTmodelarchitecture: Duetothedifferentdatagenerationmethodsandthespecialstructure of the underlying problems, we employ a different GPT architecture

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:53.030508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4f73be77-62ba-4551-8f13-470b56f723fb · outbound

This paper cites However, we do not encounter this instability in our numerical experiment, and we make an argument as the following claim.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making However, we do not encounter this instability in our numerical experiment, and we make an argument as the following claim

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.865299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a2c7d5e5-7bc9-43c3-8436-cb053a13af6e · outbound

This paper cites TX t=1 l(f(Ht),a∗ t ) # = E.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making TX t=1 l(f(Ht),a∗ t ) # = E

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.850139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d4dbda60-a734-4d43-9c38-36912b06b62e · outbound

This paper cites exploration intensity.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making exploration intensity

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.834175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 55e84a8c-246c-488e-b6be-28225b654bcf · outbound

This paper cites Thus, by the union bound, for allt≥ max{512(¯a +C)2C4 log2T √ T, 4C2 log(dT.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Thus, by the union bound, for allt≥ max{512(¯a +C)2C4 log2T √ T, 4C2 log(dT

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.818095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6fdae231-c3c6-49e0-b921-02ac838bccd3 · outbound

This paper cites C.4.5 Proofs of Lemmas Proof for Lemma C.1 Proof.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making C.4.5 Proofs of Lemmas Proof for Lemma C.1 Proof

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.801109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 44992cca-d94a-4405-8e3c-81e532d9a4ce · outbound

This paper cites For Figure 20, each subfigure is based on a sampled environment with a sampled sequence of contexts{Xt}30 t=1 from the corresponding task.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making For Figure 20, each subfigure is based on a sampled environment with a sampled sequence of contexts{Xt}30 t=1 from the corresponding task

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.638143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d1b20c94-45f0-4d04-a8e1-740e711112fb · outbound

This paper cites The optimal arm isa∗ = arg maxara.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making The optimal arm isa∗ = arg maxara

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.521545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1b53c2d4-0dcb-4424-8492-d427b087f491 · outbound

This paper cites Then right before the end of the time period, one customer will arrive with an unknown arrival rateλ.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Then right before the end of the time period, one customer will arrive with an unknown arrival rateλ

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.505225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 850fefd2-2578-4421-823c-111f550ed5fe · outbound

This paper cites D.3.2 Linear bandits • LinUCB [Chu et al., 2011]: GivenHt, we defineΣt =Pt−1 τ=1aτa⊤ τ +σ2Id, whereσ2 is the variance of the reward noise.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making D.3.2 Linear bandits • LinUCB [Chu et al., 2011]: GivenHt, we defineΣt =Pt−1 τ=1aτa⊤ τ +σ2Id, whereσ2 is the variance of the reward noise

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.379328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 05a26df9-6c9f-4662-943f-06e18c0a4a5f · outbound

This paper cites feature vector.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making feature vector

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.363587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 14161f07-2e0e-40db-a6c7-ceec325c57ac · outbound

This paper cites an unresolved cited work.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:23:52.348019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 94d35939-05b6-4c0a-b809-8d2f1d2973e0 · outbound

This paper cites Then the posterior distribution of the underlying environment is P(γi|Ht) = 1 ¯Eγi,t· ¯ϵ1−t γi P|Γ| i′=1 1 ¯Eγi′,t· ¯ϵ1−tγi′.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Then the posterior distribution of the underlying environment is P(γi|Ht) = 1 ¯Eγi,t· ¯ϵ1−t γi P|Γ| i′=1 1 ¯Eγi′,t· ¯ϵ1−tγi′

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.332109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2f55ca56-108d-455d-9aaf-05cfbbf6c700 · outbound

This paper cites E(Ht,a∗ t )∼κPγ, ˜f+(1−κ)Pγ,TFθ.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making E(Ht,a∗ t )∼κPγ, ˜f+(1−κ)Pγ,TFθ

Reference 130

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:23:52.983840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0f03b8be-775a-4a00-a5da-f609beb484ed · outbound

This paper cites Deep Neural Newsvendor.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Deep Neural Newsvendor

Reference 2001

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.238176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a243c15f-c2e0-46f9-91fa-c8eea8daab43 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Gaussian Error Linear Units (GELUs)

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.243482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d637e18-ea53-47fd-be7d-81a0bcc42dd2 · outbound

This paper cites In-context Reinforcement Learning with Algorithm Distillation.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making In-context Reinforcement Learning with Algorithm Distillation

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.260039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3038353a-1c95-41e0-93df-494f9555d5eb · outbound

This paper cites An Information-Theoretic Analysis of In-Context Learning.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making An Information-Theoretic Analysis of In-Context Learning

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.249076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78b225ef-0d79-46ed-9a2b-07779f9bddf8 · outbound

This paper cites Representing Random Utility Choice Models with Neural Networks.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Representing Random Utility Choice Models with Neural Networks

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.062421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 368da63e-7ab6-4ca9-a656-a958b0860892 · outbound

This paper cites On Dynamic Pricing with Covariates.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making On Dynamic Pricing with Covariates

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.280664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca5110f7-b4a7-4a52-a3d1-707001040070 · outbound

This paper cites Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management

Reference 2020

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:23:52.039423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e647681f-d6bc-4992-86aa-94fad1797111 · outbound

This paper cites A Neural Network Based Choice Model for Assortment Optimization.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making A Neural Network Based Choice Model for Assortment Optimization

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.356859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb6515ad-f663-4324-b0c2-0fbea9138a7d · outbound

This paper cites Is Conditional Generative Modeling all you need for Decision-Making?.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Is Conditional Generative Modeling all you need for Decision-Making?

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:50.963183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e87699a9-d85e-46f4-820d-44a38609613c · outbound

This paper cites Dynamic Pricing with Demand Covariates.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Dynamic Pricing with Demand Covariates

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.275654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d36b287-14d4-419c-b3ed-cde26125b610 · outbound

This paper cites A Survey on In-context Learning.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making A Survey on In-context Learning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.128550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 34a262e3-6c5d-4e8f-b6f1-165c292ec97a · inbound

LLM-SAA: LLM-persona Generated Distributions for Decision-making cites this paper.

LLM-SAA: LLM-persona Generated Distributions for Decision-making OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T04:01:47.660117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.