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Paper Citation Record · LEDGER

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs

As of 20 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 5 inbound Pith citation observations for arXiv:2507.03254.

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

pith.paper-citation-record.v1
2507.03254 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:19:20.707339Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:10:42.830886Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T23:13:15.688150Z

Reference resolution

24 of 24 outbound references displayed

  • verified exact1
  • verified fuzzy4
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8d52527d-4ada-4b04-9b9d-fa07f85ee92a · outbound

This paper cites Grounding llms for robot task planning using closed-loop state feedback.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Grounding llms for robot task planning using closed-loop state feedback

Reference 1

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no resolver link, observed 2026-08-06T20:19:18.661644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:18.661644Z digest=sha256:695f0dd8e38b1c208fcd4e2e17b177a62d6116abc935e76fab7358dc78861d93

Observation ffac2590-aff9-429f-b19e-d0b27d9f9d61 · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 3

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no resolver link, observed 2026-08-06T20:19:18.870999Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:18.870999Z digest=sha256:def9ab05b9987d3c85eb519cdb662a588833a6a58518a6b82d5400873fa9bb97

Observation f5e23077-5f98-4968-b45e-50c21baca477 · outbound

This paper cites Optimizing Token Consumption in LLMs: A Nano Surge Approach for Code Reasoning Efficiency.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Optimizing Token Consumption in LLMs: A Nano Surge Approach for Code Reasoning Efficiency

Reference 4

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verified exact
local_arxiv, observed 2026-08-06T20:19:21.147626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T20:19:18.967869Z digest=sha256:47f5f8ba956b6d4b3a554ea2b2104790e7cd5be05eec0ecd8e188ec5c457c68c

Observation 56c7d733-e1bc-46c7-9ee1-2127df3af9c8 · outbound

This paper cites Inner Monologue: Embodied Reasoning through Planning with Language Models.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Inner Monologue: Embodied Reasoning through Planning with Language Models

Reference 5

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no resolver link, observed 2026-08-06T20:19:19.038387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:19.038387Z digest=sha256:3dd4a045fb7951169244161509679b8ac09af94e04e16a7366bd5eafeef17106

Observation 6973003f-b030-4790-88f6-5953ea2c4d29 · outbound

This paper cites CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:19.065545Z digest=sha256:bccc25c9fed49c10d2155b7d4e3810a23a971ed95f7e7e20c5649229e985124b

Observation e077e1a1-7fc9-4ac5-8316-220bce186c8c · outbound

This paper cites GAIA: a benchmark for General AI Assistants.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs GAIA: a benchmark for General AI Assistants

Reference 8

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no resolver link, observed 2026-08-06T20:19:19.221890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:19.221890Z digest=sha256:5ff2132a7ae307309b467b217babb593c5fcf878ff2b0314dc3264663e27a64e

Observation 40ea30e3-6de1-4a8d-b841-f82f946e47de · outbound

This paper cites Virtualhome: Simulating household activities via programs.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Virtualhome: Simulating household activities via programs

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:19:21.838642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T20:19:19.353889Z digest=sha256:9f6ab8cd0c8a664e5d5a17cfdb8270edecd689cf0e80a662280dff9fbe3a7d36

Observation 1cfa8fcb-f9c7-489e-b9da-37a7103cd5a8 · outbound

This paper cites smolagents: a smol library to build great agentic systems.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs smolagents: a smol library to build great agentic systems

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:19:21.734150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T20:19:19.503021Z digest=sha256:9cbd31eb57fbc1e72ee453de708332dfb602502416ffe68982809c2dbd7a6e26

Observation 1eac347d-3966-4c14-aaa0-83feda3c27e0 · outbound

This paper cites ProgPrompt: Generating Situated Robot Task Plans using Large Language Models.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs ProgPrompt: Generating Situated Robot Task Plans using Large Language Models

Reference 12

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no resolver link, observed 2026-08-06T20:19:19.758969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:19.758969Z digest=sha256:1b3ad3a34e1a6d7c40e18ff2970a35c327707ef070bf1952991d571310680cfb

Observation fb448b1a-3a27-4d17-abe8-0ce7c936ca1a · outbound

This paper cites Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models

Reference 13

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no resolver link, observed 2026-08-06T20:19:19.825881Z

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source=pdf_text observed=2026-08-06T20:19:19.825881Z digest=sha256:93049e91b8e645e532ae1006fa916b9e97ab329e0f350c9e362b93dc520c8f32

Observation 2b351813-1090-489d-ab55-cc4679f4cc39 · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 14

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no resolver link, observed 2026-08-06T20:19:19.696047Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:19.696047Z digest=sha256:bad32b79b0d85c0613fff7f46ab0a5ffb6927bb06d60a1bc7cf3c441f5ae4f63

Observation f236aac4-1ec8-4d6d-b329-0c0b035db0da · outbound

This paper cites Executable code actions elicit better llm agents.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Executable code actions elicit better llm agents

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:19:21.593153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T20:19:20.044158Z digest=sha256:99568ccd966a48b31f6d8382e7b26d30ea4cd6f288f34ad7684315fe410dfc50

Observation a5a3d8fe-8f36-4e44-b94f-8deecbe99c67 · outbound

This paper cites Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent Systems.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent Systems

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:20.136505Z digest=sha256:9a51207071dfbee94a5f05d4830b3005e2dee822409ab9ce42c1a64919235e2b

Observation 125182e7-3b1e-436a-ae2e-34b4583b1a70 · outbound

This paper cites MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs

Reference 17

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no resolver link, observed 2026-08-06T20:19:19.906336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:19.906336Z digest=sha256:0a1473348d2cdbe9a32048efae9d2e15186d42213f33b4a1b3b9195679890a37

Observation a7d88685-6bb0-4bae-8516-548b4fe424d7 · outbound

This paper cites Unlocking Reasoning Potential in Large Langauge Models by Scaling Code-form Planning.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Unlocking Reasoning Potential in Large Langauge Models by Scaling Code-form Planning

Reference 18

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no resolver link, observed 2026-08-06T20:19:20.300033Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:20.300033Z digest=sha256:226c009e439e388d91a30bde4aaee82f05a468f190305d930b6a65d0ebee30bb

Observation fff86044-0235-457d-8b3e-8c644acc40c9 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 19

Resolution
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no resolver link, observed 2026-08-06T20:19:20.389189Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:20.389189Z digest=sha256:6936cb55fa9ba606e2ef0f2272cea67bc1ca5152ccba9292000342783f94e41e

Observation 1666cf00-7120-4e1a-998d-099305bd94d6 · outbound

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

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 20

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no resolver link, observed 2026-08-06T20:19:20.208590Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:20.208590Z digest=sha256:6d72d257856f5b08ba03722204c9ce8138abebfdbbb7cbb55619698e5d37c186

Observation 6aa398d1-cbc9-4d72-9ad6-2aa8b986720b · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs ReAct: Synergizing Reasoning and Acting in Language Models

Reference 21

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source=pdf_text observed=2026-08-06T20:19:20.475651Z digest=sha256:a87ea7de920ef89bdb89af401b4250e453a9b39c697affd0496d110a7dd8a2d6

Observation 5c7635ac-7183-4fdb-9c41-48d1adc4a1d9 · outbound

This paper cites Cohen, Ruslan Salakhut- dinov, and Christopher D.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Cohen, Ruslan Salakhut- dinov, and Christopher D

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:19:21.394560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T20:19:20.442323Z digest=sha256:c357be207986c7ffe482bcce7f04429e5223fe06364d7d3261d4bc997847e88c

Observation ebb0946f-dda3-43fa-ad22-8ee8241310c6 · outbound

This paper cites Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

Reference 24

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no resolver link, observed 2026-08-06T20:19:20.707339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:20.707339Z digest=sha256:715f187d2f1dac3f95d2ed15e0b31e413f097e975c5586aecdafd276d9bee120

Observation 67e51e3c-28e8-48e6-8fe9-5f91fff28bf0 · outbound

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

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 26

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source=pdf_text observed=2026-08-06T20:19:20.630478Z digest=sha256:cc18fa23c414e91efa763b8c57aab3770abcd2417039152eec5f00e3b085bf89

Observation 6d74b4e5-1871-499b-8e94-8c889897e719 · outbound

This paper cites Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Reference 27

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:20.670254Z digest=sha256:df8f047e8441707a9a310358edcc9cf28f6b0109c21bc62242d2f0900fabd5cb

Observation 2dc026af-f8fb-4d1d-b7f2-3673d128266e · outbound

This paper cites PAL: Program-aided Language Models.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs PAL: Program-aided Language Models

Reference 2023

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no resolver link, observed 2026-08-06T20:19:18.803952Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:18.803952Z digest=sha256:c85c5360b9e19fada03e05cf0bc22b02a403d0dbf5dcf73261105d3df636ac07

Observation 5b08bec4-baab-43d2-b992-3818850b1bb7 · outbound

This paper cites Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models.

CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Reference 2024

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:19.140622Z digest=sha256:8d07b5b1741ee0c6ab1461bfb216ac8778e4d1283a3c2dd8a262319bcbca8633

Pith citing papers

Observation ff148a5c-9452-4b79-baf6-64b459be45ff · inbound

Tractable Asymmetric Verification for Large Language Models via Deterministic Replicability cites this paper.

Tractable Asymmetric Verification for Large Language Models via Deterministic Replicability CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs

Reference 2025

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no resolver link, observed 2026-08-04T17:10:42.830886Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:10:42.830886Z digest=sha256:9d4d26b30e0950cf4488228571d7aad213a9a056a2be4e946d7318bd6d14d6c4

Observation 685d619e-e007-4560-8952-a4fee476bb04 · inbound

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory cites this paper.

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs

Reference 236

Resolution
verified exact
arxiv_id, observed 2026-05-14T23:13:15.691012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-14T23:13:15.016486Z digest=sha256:c5b996e2464f78505812341af951bab6b483d01bee20117c85f048754609dab6

Observation c9c64c28-bed3-42b4-a120-d1dbd92b7e41 · inbound

Toward Efficient Agents: Memory, Tool learning, and Planning cites this paper.

Toward Efficient Agents: Memory, Tool learning, and Planning CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs

Reference 167

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no resolver link, observed 2026-08-03T09:21:47.700265Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:21:47.700265Z digest=sha256:65bd8949ea4e1844fda27b10f844e872eabb786a58ad489a41b727df29075448

Observation d4eb831b-dddf-4efc-84c2-6b5b990e7aec · inbound

Token Economics for LLM Agents: A Dual-View Study from Computing and Economics cites this paper.

Token Economics for LLM Agents: A Dual-View Study from Computing and Economics CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs

Reference 109

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T07:31:27.497041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-12T02:34:34.546971Z digest=sha256:99eb606fe27544ed2bc342f73828baeff46034671eb0ac5e61c302f75c98b5fc

Observation bcc6e4bd-d1de-4880-813e-a99d24844017 · inbound

The Best Programming Language for Tokenmaxxing: An Investigation of Coding Agent Behavior Across Programming Languages cites this paper.

The Best Programming Language for Tokenmaxxing: An Investigation of Coding Agent Behavior Across Programming Languages CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs

Reference 14

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no resolver link, observed 2026-08-01T04:41:31.264767Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T04:41:31.264767Z digest=sha256:4062e26f9b92df954ea1799625311d156e2186aad7c2c67728eba38708f1d7fe