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Paper Citation Record · LEDGER

TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2309.03736.

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

pith.paper-citation-record.v1
2309.03736 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 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 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:26:38.493885Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:09:54.468733Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 56e4e5ba-4578-4db1-bd54-064c2bd88957 · inbound

A Survey on the Memory Mechanism of Large Language Model based Agents cites this paper.

A Survey on the Memory Mechanism of Large Language Model based Agents TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 154

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:21:39.627093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-15T07:21:39.440092Z digest=sha256:d06ece88b4aeef5aff6d3b0dd7788e28893edabc1d863481e947d5a693641fc5

Observation d7891205-fad4-48fb-a4bf-b74c206c7ab4 · inbound

From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents cites this paper.

From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 182

Resolution
unresolved
no resolver link, observed 2026-08-11T22:18:32.198740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:18:32.198740Z digest=sha256:ec4414d078e7f8e4cc25284ec52fa4ccf63fa8f5eea0f73147d1d560cbf06ec2

Observation 60aa2ecf-f116-4e0a-8824-07ea930e9839 · inbound

A Plug-and-Play Natural Language Rewriter for Natural Language to SQL cites this paper.

A Plug-and-Play Natural Language Rewriter for Natural Language to SQL TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T05:53:02.335749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:53:02.335749Z digest=sha256:a55d40f28f620f9bcfa0ba11f63809ad180f5b334511e245d7dede15e4d39c27

Observation d0bdbbce-950c-4974-a7d2-e1650d0242e3 · inbound

Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learning cites this paper.

Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learning TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T05:12:11.301981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:12:11.301981Z digest=sha256:9ad8c161906e1552be867ce06ef780419a026c41555b550a047ec840f1318de5

Observation 24f4d0a4-ab1c-4d8c-98b4-f7d891b19295 · inbound

Do as We Do, Not as You Think: the Conformity of Large Language Models cites this paper.

Do as We Do, Not as You Think: the Conformity of Large Language Models TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-10T16:16:52.819223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:16:52.819223Z digest=sha256:e16bac2f612592082ef781a9764bf81366ba1aa9d6bfa7dbfa9ebe79dce4225b

Observation 61ebab2a-dda3-4458-bf3f-893261a7ad31 · inbound

Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews cites this paper.

Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-08T19:23:59.871002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:23:59.871002Z digest=sha256:d79dd83119fc51ee032781e0ebe2452a58a9e96209995c63408609ddc5899755

Observation 2a786ac2-118a-4e0e-a5af-1d02a255a2de · inbound

FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting cites this paper.

FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:52:26.559899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-23T02:49:40.277048Z digest=sha256:5b47fc62ec7f58d624a957756c209095ce14998a799c6e1e3a0ed4096ec26f7c

Observation 7987977e-e1c9-4ac5-9707-c60ecfd717e7 · inbound

Large Language Model Agent: A Survey on Methodology, Applications and Challenges cites this paper.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 294

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.544056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:4ced50c819a087c6b373d62e4ca2228c1117238124260884da1c275d160d5749

Observation 44ab68b5-dc4f-4723-a284-5b32d5667c51 · inbound

From Human Memory to AI Memory: A Survey on Memory Mechanisms in the Era of LLMs cites this paper.

From Human Memory to AI Memory: A Survey on Memory Mechanisms in the Era of LLMs TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-17T11:05:09.744779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-17T11:05:09.588491Z digest=sha256:0f852918fe1dde7877aae65c489d128e3e7bd02d301a53714844a64d7a3f0e49

Observation 277623c5-89b1-44f7-b3f6-822e403f9c92 · inbound

Maris: A Formally Verifiable Privacy Policy Enforcement Paradigm for Multi-Agent Collaboration Systems cites this paper.

Maris: A Formally Verifiable Privacy Policy Enforcement Paradigm for Multi-Agent Collaboration Systems TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T23:26:38.493885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:26:38.493885Z digest=sha256:31e4e5808cd39231a75b8dfbac17d8db8ddf7d0269dcf89d87f20cfabdbb2bfb

Observation 6fd76012-0cc6-4b3e-ac42-e9d55ef94401 · inbound

LLM-Powered AI Agent Systems and Their Applications in Industry cites this paper.

LLM-Powered AI Agent Systems and Their Applications in Industry TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-22T14:06:37.855203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-22T14:05:54.535411Z digest=sha256:30143375620fcaa18b7d6e043044a4b3864aa80484b9b516035832e4f3ec7621

Observation 00736b61-2dbf-4cdd-a8fc-d78634cf2ab1 · inbound

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets cites this paper.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:22.596425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:22.596425Z digest=sha256:724123235583934b02fb1b9b7666efdd52894c4d8d37cdc05de045ddfc376ec0

Observation 1962d965-c2a9-44db-8c25-6967305bcde5 · inbound

Efficient Leave-one-out Approximation in LLM Multi-agent Debate Based on Introspection cites this paper.

Efficient Leave-one-out Approximation in LLM Multi-agent Debate Based on Introspection TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T13:16:20.583371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:16:20.583371Z digest=sha256:513d6715377849d92cd39765060ef4b8c36e8efeadd12ee3acec8085bd260ffe

Observation c9138890-dced-4e21-bf5e-b70bcb61d2fc · inbound

Doc2Agent: Scalable Generation of Tool-Using Agents from API Documentation cites this paper.

Doc2Agent: Scalable Generation of Tool-Using Agents from API Documentation TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T23:05:09.554803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:05:09.554803Z digest=sha256:cb9a7af94153c40cbfab11f955e83c1558cca35ff38b146f684791db3112e756

Observation 511a3013-1482-450d-a059-7669b3110af9 · inbound

To Trade or Not to Trade: An Agentic Approach to Estimating Market Risk Improves Trading Decisions cites this paper.

To Trade or Not to Trade: An Agentic Approach to Estimating Market Risk Improves Trading Decisions TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T18:22:15.824389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:22:15.824389Z digest=sha256:392b1c1c65d5453a64fa1965f3218964a38f41b27b8d68ab7bf25975d7af2412

Observation 274edb4e-0158-4d73-875f-a848a24096be · inbound

FinTeam: A Multi-Agent Collaborative Intelligence System for Comprehensive Financial Scenarios cites this paper.

FinTeam: A Multi-Agent Collaborative Intelligence System for Comprehensive Financial Scenarios TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T20:02:14.160845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:02:14.160845Z digest=sha256:a916ab78d5b9054097b56955828d86ebdedc2f379fffe8c6c981271ca2c389fc

Observation 37b183e5-1487-4e34-9e3c-c2a9bbb783fd · inbound

ContestTrade: A Multi-Agent Trading System Based on Internal Contest Mechanism cites this paper.

ContestTrade: A Multi-Agent Trading System Based on Internal Contest Mechanism TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T10:12:19.808982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:12:19.808982Z digest=sha256:2521d31b6f637527d463fca63d5986a65d58cec7178ab9293cac4a85401829ae

Observation 483fdc68-ab5a-4950-bf88-1fa0b87de80d · inbound

Forecasting Commodity Price Shocks Using Temporal and Semantic Fusion of Prices Signals and Agentic Generative AI Extracted Economic News cites this paper.

Forecasting Commodity Price Shocks Using Temporal and Semantic Fusion of Prices Signals and Agentic Generative AI Extracted Economic News TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T14:35:42.123602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:42.123602Z digest=sha256:4d5758e0c5980882d302415d57732f8cc125923cc72665df15796d48d0833763

Observation 26c9f5c0-f458-4a2d-8cdc-68ab1cfd9e97 · inbound

SHARP: A Self-Evolving Human-Auditable Rubric Policy for Financial Trading Agents cites this paper.

SHARP: A Self-Evolving Human-Auditable Rubric Policy for Financial Trading Agents TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:06:04.018699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-11T00:51:53.252358Z digest=sha256:1e2bff2c1c4e64548b1881c582cffad6aed9fb37cbbde3c4018c94a83e8c5ae5

Observation 03484088-9cb1-4c0a-a8f8-6ff2bf69d3f1 · inbound

Is a team only as strong as its weakest link? Quantifying the short-board effect with AI Agents cites this paper.

Is a team only as strong as its weakest link? Quantifying the short-board effect with AI Agents TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T02:30:55.347619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-11T02:28:49.522313Z digest=sha256:491ca1e9ac68cf867fd233ce431e3fa707928858237a6fbe22ff562a251f9dfc

Observation bbce3a00-3bfa-4ebc-b064-d9c2b5006767 · inbound

MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models cites this paper.

MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:25:23.362382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-25T05:24:05.098181Z digest=sha256:41c3271ccb9ffacf6e60b415e56230789352aadaabbe3d0ddfb82bce879b5817

Observation 7e4a5570-ffe1-4018-8f51-b4309649f91d · inbound

PandaAI: A Practical Agent CQ2 for Neuro-symbolic Data Analysis And Integrated Decision-Making in Quantitative Finance cites this paper.

PandaAI: A Practical Agent CQ2 for Neuro-symbolic Data Analysis And Integrated Decision-Making in Quantitative Finance TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-02T16:17:09.260277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T22:50:14.845721Z digest=sha256:ada7cb2bf7020d5c39f482037ccd977c84c9a3f667319859202d191c73673781

Observation 1fd1fb4b-6568-49b3-bda2-1260af3cd6f8 · inbound

Beyond Agent Architecture: Execution Assumptions and Reproducibility in LLM-Based Trading Systems cites this paper.

Beyond Agent Architecture: Execution Assumptions and Reproducibility in LLM-Based Trading Systems TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-02T21:37:25.623496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T19:35:11.289439Z digest=sha256:85ee84e11643888af60416c709080c47801fe8328fc5aebfc36e1076c8807d89

Observation bb68ee89-2853-4d43-a932-058f03188a8a · inbound

AlgoEvolve: LLM-driven Meta-evolution of Algorithmic Trading Programs cites this paper.

AlgoEvolve: LLM-driven Meta-evolution of Algorithmic Trading Programs TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-04T15:09:54.470801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T01:53:05.638642Z digest=sha256:e5ad18698e2d01cc49f8114b1c92a3efe911ffc473d46660c7e4e2450d2e833a

Observation 62a9b0fa-9077-4042-a942-2a3215beff6d · inbound

OpenPM: Auditable Point-in-Time Evaluation for LLM Portfolio-Management Agents cites this paper.

OpenPM: Auditable Point-in-Time Evaluation for LLM Portfolio-Management Agents TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-12T00:57:03.554442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:57:03.554442Z digest=sha256:e3a0e891e79d2f91c0954325300be761944356aacff7f49cfb9eb68ebd9c478d

Observation 23dcb5ef-1c37-4d10-bcb8-d747561bba66 · inbound

Beyond Cash Flows: A Multi-Agent AI Framework for Valuing Clinical-Stage, Cross-Border Biotechnology cites this paper.

Beyond Cash Flows: A Multi-Agent AI Framework for Valuing Clinical-Stage, Cross-Border Biotechnology TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T04:16:27.453401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:16:27.453401Z digest=sha256:426fb382255b6e4be2b7e8c2d25e853d4e23a6e325a77b3d69156e965ffaed2c