Paper Citation Record · LEDGER

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles

As of 16 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2411.19515.

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

pith.paper-citation-record.v1
2411.19515 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:09:45.635340Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

30 of 30 outbound references displayed

verified exact1
verified fuzzy11
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f7689c7f-00de-4347-a737-dcd15341188e · outbound

This paper cites Company Similarity using Large Language Models.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Company Similarity using Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.437375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21a6bac5-1169-49ed-84f2-c6ebb1879649 · outbound

This paper cites Enhancing Knowledge Graph Construction Using Large Language Models.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Enhancing Knowledge Graph Construction Using Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.443536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14b34460-d5ef-4ea1-b747-feccb3e93549 · outbound

This paper cites Accounting fraud detection using contextual language learning,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Accounting fraud detection using contextual language learning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.540086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d4a18e19-359c-4cd2-b234-2f672ce2fb27 · outbound

This paper cites A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.455359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc768a6c-dd73-45c0-b92b-365354cc2d28 · outbound

This paper cites Can ChatGPT improve investment decisions? From a portfolio management perspective,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Can ChatGPT improve investment decisions? From a portfolio management perspective,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.514252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3901a2b9-88cf-4e25-8de9-808aad85f58c · outbound

This paper cites ChatGPT-Based Investment Portfolio Selection,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles ChatGPT-Based Investment Portfolio Selection,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.491952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7e536f62-2565-45c4-8e83-5c94c7e798e4 · outbound

This paper cites GPT’s idea of stock factors,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles GPT’s idea of stock factors,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.465827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1e7f9f51-2c97-4825-b989-71a0c116a538 · outbound

This paper cites Barber and T.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Barber and T

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.443541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4debe036-d791-40fa-8231-f7e647d9c5d4 · outbound

This paper cites Institutional investors,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Institutional investors,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.421516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 24eddbae-d250-478a-9d48-cd2bfd9a53e8 · outbound

This paper cites The influence of gender on the perception and response to investment risk: The case of professional investors,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles The influence of gender on the perception and response to investment risk: The case of professional investors,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.394160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 28990d75-7a0b-419e-b52b-b3b555cc4ed6 · outbound

This paper cites Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.505572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d62adf8a-dea4-4c9a-8c09-0314738b33ed · outbound

This paper cites ExpertPrompting: Instructing Large Language Models to be Distinguished Experts.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles ExpertPrompting: Instructing Large Language Models to be Distinguished Experts

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.512040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3eca731c-24f5-4fbc-83d5-58390b9eb802 · outbound

This paper cites Large Language Models Perform Diagnostic Reasoning.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Large Language Models Perform Diagnostic Reasoning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.517932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb906ee2-b8d0-43bf-a23e-3ca0ab543864 · outbound

This paper cites Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.523944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6e70ada-38de-4e56-92c2-7a16bdc00ec8 · outbound

This paper cites Can ChatGPT reduce human financial analysts’ optimistic biases?,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Can ChatGPT reduce human financial analysts’ optimistic biases?,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.365690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f9f84a80-b531-4f35-b24e-347156428075 · outbound

This paper cites Analysis on Enhancing Financial Decision- making Through Prompt Engineering,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Analysis on Enhancing Financial Decision- making Through Prompt Engineering,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.339432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d38983e8-0b84-4027-8c89-9eb87b842177 · outbound

This paper cites Democratizing Financial Knowledge with ChatGPT by OpenAI: Unleashing the Power of Technology,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Democratizing Financial Knowledge with ChatGPT by OpenAI: Unleashing the Power of Technology,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.319445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3cb0d059-5cf7-4157-a6a6-0e9fee7c7fb6 · outbound

This paper cites GPT-4 Technical Report.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles GPT-4 Technical Report

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.550804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 279560f1-d60b-4908-acee-6e8963e19165 · outbound

This paper cites Best practices for prompt engineering with the Ope- nAI API,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Best practices for prompt engineering with the Ope- nAI API,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.558422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec9560e3-1be5-4084-9c7e-026e23b4c6f1 · outbound

This paper cites Prompt engineering,.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Prompt engineering,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:09:46.298015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e3f9616-a7e5-4907-8865-610b8f64e1b0 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.572128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c4f96f2-b598-41d5-93d6-07731f1fdea9 · outbound

This paper cites Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.578617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9fef04f-f071-4bd6-bdcb-8ca99550519e · outbound

This paper cites Large Language Models are Zero-Shot Reasoners.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Large Language Models are Zero-Shot Reasoners

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.585554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c113bbf2-e672-4005-9bc3-e6222dedf2e9 · outbound

This paper cites EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.591656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 486fb320-72d8-4c50-8afc-60a0100569ce · outbound

This paper cites Language Models are Few-Shot Learners.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Language Models are Few-Shot Learners

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.600326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 885105b5-35cb-41e6-985b-e6ac9e882f70 · outbound

This paper cites Contrastive Chain-of-Thought Prompting.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Contrastive Chain-of-Thought Prompting

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.608314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd1f67db-0fb4-473d-a340-9ea9685c5731 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.615715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3f8851c-d703-4113-bfc8-b1d408f0d7c5 · outbound

This paper cites Self-Refine: Iterative Refinement with Self-Feedback.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Self-Refine: Iterative Refinement with Self-Feedback

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.621781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c0f8f25-85e6-4e85-b60b-0e0d1249e72f · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T10:09:45.628866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e921fc35-23c0-414d-8730-32ccc66b8ccd · outbound

This paper cites Hierarchical Narrative Analysis: Unraveling Perceptions of Generative AI.

Leveraging Large Language Models for Institutional Portfolio Management: Persona-Based Ensembles Hierarchical Narrative Analysis: Unraveling Perceptions of Generative AI

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-12T10:09:45.701192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.