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Paper Citation Record · LEDGER

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As of 9 August 2026, this Paper Citation Record lists 97 of 97 outbound references and 8 inbound Pith citation observations for arXiv:2505.17716.

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

pith.paper-citation-record.v1
2505.17716 v1

Coverage vector

measured 97 of 97 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:44:31.351435Z

measured 105 of 105 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:34:58.922731Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:58:57.420819Z

Reference resolution

97 of 97 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved91
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 41e24c31-b48e-45b1-a0c3-278b44f01992 · outbound

This paper cites Workflow Use.

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Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:21.623706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:21.623706Z digest=sha256:c9e72de6a619e7bebac022e262f97f0b7ffe4b04aa44d416a1add9035107a568

Observation 92430e5d-8a27-48fe-abc1-fc56bd17bfc3 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:21.716221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:21.716221Z digest=sha256:e703a2651015c18d6d8d4d2e734e81c486b6c4f4b1351ede6103e0495c988fbc

Observation cfed8277-e996-4e49-96fb-f262de392385 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:21.820445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:21.820445Z digest=sha256:c7735c0334f3cab70edf709e74d36935f8de07f96efc5bcef2f61afb2139d697

Observation bc0d75a4-8308-4dae-9f35-f895117136e7 · outbound

This paper cites AirGapAgent: Protecting Privacy-Conscious Conversational Agents.

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Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:21.931565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:21.931565Z digest=sha256:cea2bde7205905f2a7e1e055ce72652a5e846914da662e9f8d42ac019c8bd9c1

Observation 37cc5a43-6b71-4efe-8d4f-bb11ff46f010 · outbound

This paper cites LLMs Will Always Hallucinate, and We Need to Live With This.

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Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.019183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.019183Z digest=sha256:09037d8e2a065161664cf4774165d4f9b1ad6932f1b6da19d0cc40ffbb753bd2

Observation 537e038e-01fe-445b-a2dc-992b621933fa · outbound

This paper cites SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning.

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Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.092192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.092192Z digest=sha256:17d93d9ba9c4f322acb0e2549093484710e9ed5ffa758cacc66550dae9761577

Observation 630895a8-50c6-4bbc-b73f-3489133076ea · outbound

This paper cites Fine-Tuning Large Language Models with User-Level Differential Privacy.

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Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.165394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.165394Z digest=sha256:7fbfcf9d80d4ce8b8561377ac12082f72539c1ff5a6fa8e3a01ff631397dd0ce

Observation 150a8806-5a0c-47bd-bad3-3e2fe54f5d5d · outbound

This paper cites The Obvious Invisible Threat: LLM-Powered GUI Agents' Vulnerability to Fine-Print Injections.

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Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.237391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.237391Z digest=sha256:5001263f1cdaace5a933f14e29f60daaae78a4b38db45d73ba5baa15797e91f7

Observation 66a16f67-897b-4287-ab90-c37253fd370d · outbound

This paper cites CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis and Risk Generation for Large Language Model Applications.

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Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.342841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.342841Z digest=sha256:009ec42e643e0648e4c3bf3666439607ccd870a71902389a3295b23d9499dc71

Observation 4d8aec58-7fdd-49aa-be59-a69587955790 · outbound

This paper cites ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning.

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Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.442472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.442472Z digest=sha256:7d636cd5e96e462eaf3eb859ce6b4670e65d5e42b8ee61670df7d67eedaf57c9

Observation 915c38dc-f076-4c53-95d6-34ba436c3669 · outbound

This paper cites Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory.

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Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.533849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.533849Z digest=sha256:109d0cca607b4da05440f30945657a4d632e668de4334a51d14e761d54b06864

Observation b0f46c86-94f2-4f03-aeb7-17cae6fcdc37 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.610417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.610417Z digest=sha256:7d5ea733aac4af3db23a04db373158a86a148c6b2ababa2830866034d7c17858

Observation a0a4f8b2-b913-4353-b3f2-940c93926836 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.701647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.701647Z digest=sha256:d968e5473404849679961b3d40bb4bde8a1df08f540a65d735770bb77f5b7a29

Observation af0f196e-a1bc-4f49-ab37-ddb967b841a0 · outbound

This paper cites Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents.

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Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.864946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.864946Z digest=sha256:f3282d825a1c8fc075dfffe0c0c671af931e7db67439f25d583c7b0c065f8149

Observation dd70692f-3659-4cc7-b7ed-77ea7467f4f4 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.015401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.015401Z digest=sha256:e021916cb4c180303bbfff99e438eebfe4a414966bdfdc53021cb458efbbcdc7

Observation 0d10b42b-515c-40a5-b47a-0fafba6430f3 · outbound

This paper cites Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster.

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Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.116345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.116345Z digest=sha256:87275c964d4d9f424f9431d5244e3385c5cd18644d6e08a560ff21301617ff91

Observation 7b6c9bad-d0d5-4c83-be8e-559423637ada · outbound

This paper cites Building Guardrails for Large Language Models.

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Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.169749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.169749Z digest=sha256:a9f34684bf264d5273dd52ddf097c660400520c637e55d2209ed5b1a54e4aa31

Observation aac9bb44-f36d-488a-8da0-8cff6d5dd7b3 · outbound

This paper cites MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design.

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Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.206783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.206783Z digest=sha256:a6e73cc185e30eabf5dee1ff9564eef315b6468b3d86f073b62fa5c976460d6d

Observation d5453964-4ae2-4241-9deb-9ad9132be92a · outbound

This paper cites ReTool: Reinforcement Learning for Strategic Tool Use in LLMs.

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Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.211372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.211372Z digest=sha256:327ce0b45078604eef5c20f5e74d36b0f96b41402fb74414d165e463b2e31326

Observation 221c8c36-5f1a-46d6-b59c-745ce941af8e · outbound

This paper cites Towards Efficient Record and Replay: A Case Study in WeChat.

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Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:44:34.145798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:44:23.216049Z digest=sha256:83d7c2d0cb5e8d1ed3ef9c623cafc32c0cb32edab9464907e3096af979f9cf70

Observation 7d9a689a-d348-4f41-ba2b-8d9e55855340 · outbound

This paper cites I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders.

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Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.234479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.234479Z digest=sha256:9ce13940167820382b474a588b35e509c34d60c0113c54e9c8294a25a9317893

Observation 15bb2341-a93d-415d-9512-251a6bfc6e8e · outbound

This paper cites Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey.

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Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.275355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.275355Z digest=sha256:7e4eea6390e5d741fccd6581f312620df0b41cd8d82b5a21d99dca3ea98709a2

Observation a6c0d282-3272-4465-ae5b-ae389312df35 · outbound

This paper cites A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models.

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Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.313148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.313148Z digest=sha256:fb735394d11a611971b0c0190b20e4406704a1ecdb52cb9909ace119e84533dd

Observation 71362ded-996a-4e10-8c80-66dfb4b9f1e6 · outbound

This paper cites Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use.

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Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.355764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.355764Z digest=sha256:255b788f3a641e20caa2f1f92c8b0bfc0084c8092ab898da108e29ffad8aa1c8

Observation 5dc8f669-2a0f-4665-bcb2-bdb81f2ed371 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.431178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.431178Z digest=sha256:91c57841315b6a5b2a44e2e75e72671c90c068aecef98916453a3ac915a7505c

Observation e167ea5a-9c88-4604-b656-1a484180d665 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.514961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.514961Z digest=sha256:e60d18dce7aa36e213b6941901967112e1f21bba57ac21062cbfda0ce4749e63

Observation 358b56e5-8dae-4abc-aa35-e0cbf2f7b780 · outbound

This paper cites MiniLLM: On-Policy Distillation of Large Language Models.

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Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.608742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.608742Z digest=sha256:1ad4831a07fc8976024f29ed49671d551d41330fb671c71eb702ff644ff6a97e

Observation 17075482-ebc7-4d9a-8339-7625d35d6f50 · outbound

This paper cites Building A Secure Agentic AI Application Leveraging A2A Protocol.

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Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.743076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.743076Z digest=sha256:c410f76b657a84dbc1d1b6fa063e2a71b88c57232ffb8e18dbc71b5179b2a68b

Observation 3a0cb11b-a5c1-4def-8d58-2e337b8d1272 · outbound

This paper cites Bridging the Safety Gap: A Guardrail Pipeline for Trustworthy LLM Inferences.

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Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.855111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.855111Z digest=sha256:f179edb89641b89abc5349ff6a70f2d8cf50b3a3f502c25c95daf914dcee1749

Observation 5c6e9611-ed64-4256-9730-dffd85d5381e · outbound

This paper cites Instruction-Following Pruning for Large Language Models.

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Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.951879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.951879Z digest=sha256:8316e304369fa1aa31bd5784a0c0afead2b056bfbe84b9c1c880d78a146def52

Observation 8a210463-3589-4c08-86ec-15b7e6b12de1 · outbound

This paper cites Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions.

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Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.064474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.064474Z digest=sha256:56758bfe11af80cb93887e2967244891f55c0d05cc86ca6c070369cf0db65165

Observation eaf7abcf-b213-444e-ba90-3a13148a4ce0 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay LoRA: Low-Rank Adaptation of Large Language Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.144513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.144513Z digest=sha256:51699e7368f2fd0e5b5f3364b198e0de77439d5c6a930e18ec4573f7c0db2cc3

Observation 014c392e-13c8-4eab-9ee7-206eeae34f76 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.254468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.254468Z digest=sha256:1c0260dc56f401577caaed2ae912ca857938589b4a27d5d119b4040fb4df878d

Observation 9d92ee5a-d4ce-4cc8-a074-cf5e180bf1fd · outbound

This paper cites R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory.

Get Experience from Practice: LLM Agents with Record & Replay R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.367410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.367410Z digest=sha256:9ea92b27cd791fa21c226f70885a0cfe6978cddb192b7799e0d5d5987ff8b261

Observation 14482955-bc17-4358-9bad-7c5ecaf83bed · outbound

This paper cites $R^2$-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning.

Get Experience from Practice: LLM Agents with Record & Replay $R^2$-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.482001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.482001Z digest=sha256:c7846f38b3c5cd6dd320658e0ff23e986a749c13d290b4d605c141ebb477bdb5

Observation 5f4a6291-f63f-4143-b89b-bbc4ec90e402 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.563126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.563126Z digest=sha256:c2530f41e32f441bce4fa04b0c403961c87e0e484c97f5580c21078307af925a

Observation b30c4fe7-afb1-4d22-82df-1120b9428702 · outbound

This paper cites When LLMs Go Online: The Emerging Threat of Web-Enabled LLMs.

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Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.672026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.672026Z digest=sha256:9018bbaf8a7144072311c1db929252dfb647048676f6d907de161ba7094a68d3

Observation d5a9528f-ad38-4fe6-8863-8c0d42c8ee3a · outbound

This paper cites LoRA-Switch: Boosting the Efficiency of Dynamic LLM Adapters via System-Algorithm Co-design.

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Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.752407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.752407Z digest=sha256:55b88338a2807c5b2ee00c7ca1cef3a0f422a7a4e106ad7b33c93fcf3f3656fd

Observation eb9bb32d-f13b-4a16-9207-cc8a9472e4db · outbound

This paper cites RT-Cache: Training-Free Retrieval for Real-Time Manipulation.

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Reference 39

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source=pdf_text observed=2026-08-07T14:44:24.896006Z digest=sha256:b428251f94d7b121046314ac255b7d5b22e3ede36860e0f6acd4796d54ce359e

Observation d749a6c7-5ef3-4ab9-ac50-8e7498fd0572 · outbound

This paper cites an unresolved cited work.

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Reference 40

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source=pdf_text observed=2026-08-07T14:44:25.024385Z digest=sha256:5a562e7a276568110165ee311009caf4622495243511aff8880ef06bfd07ed2a

Observation ee62f678-68e6-41f9-9d17-d5186a03d75d · outbound

This paper cites TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models.

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Reference 41

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source=pdf_text observed=2026-08-07T14:44:25.216265Z digest=sha256:357933150108471e243fb4e340a9a59102e4b55ed4b0e4a356b553dc545bcf43

Observation cd5a48d4-84d6-4b8e-bd54-1cf25659c5cf · outbound

This paper cites ACE: A Security Architecture for LLM-Integrated App Systems.

Get Experience from Practice: LLM Agents with Record & Replay ACE: A Security Architecture for LLM-Integrated App Systems

Reference 42

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source=pdf_text observed=2026-08-07T14:44:25.389219Z digest=sha256:442ac81a3ff4daf4e487a616eb11251610d9775c72beb517a2760ba08adb644b

Observation a02fb9e6-cee7-453c-8c60-da1e8f7e2227 · outbound

This paper cites Enhancing Retrieval-Augmented Generation: A Study of Best Practices.

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Reference 43

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source=pdf_text observed=2026-08-07T14:44:25.538757Z digest=sha256:b883c0a4aad74614451be2987fbaa63ac89634676786b91da0fc5b998885f8f7

Observation 57fa5b82-10af-4c2f-b971-88517283d9f4 · outbound

This paper cites Large Language Models Can Be Strong Differentially Private Learners.

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Reference 44

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source=pdf_text observed=2026-08-07T14:44:25.655123Z digest=sha256:c31e9702b4f80238d95bd036e83c084ceb7c5b9b41b6a71c0b8bcea01e063fea

Observation 32e9b4c8-21d2-40d7-8ce9-9937ff5f51b5 · outbound

This paper cites Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models

Reference 45

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source=pdf_text observed=2026-08-07T14:44:25.766462Z digest=sha256:0eac822ede442f51abd2c7fd2c6010a39529045c5c42d045dd38839bb46a421f

Observation 7af17398-9292-4b95-bbac-022fd8ff71d5 · outbound

This paper cites Gonzalez.

Get Experience from Practice: LLM Agents with Record & Replay Gonzalez

Reference 46

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source=pdf_text observed=2026-08-07T14:44:25.908238Z digest=sha256:b32ea96bbac9e4c843cf9082f1a6c7ae436850a08d5bcd1e9ef09c91c575afa5

Observation d61d0b48-e320-44d0-bb49-18904d608e4d · outbound

This paper cites SlimGPT: Layer-wise Structured Pruning for Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay SlimGPT: Layer-wise Structured Pruning for Large Language Models

Reference 47

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source=pdf_text observed=2026-08-07T14:44:26.235980Z digest=sha256:7a87b363e67a6b2eb1ef16a8e87ea6762b53354f5b85a97237e6d9a9949d3d7a

Observation ee0dd90a-7894-499a-bf0b-e341fb3c6c2b · outbound

This paper cites Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems.

Get Experience from Practice: LLM Agents with Record & Replay Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Reference 48

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source=pdf_text observed=2026-08-07T14:44:26.359633Z digest=sha256:eb05ea6b3ce0c0ec9d3e18ff33231ecdfce938e33642e95c888813d03c48bdd3

Observation d503717f-c057-4032-bd8e-ebc1324605e7 · outbound

This paper cites Efficient Inference for Large Reasoning Models: A Survey.

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Reference 49

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source=pdf_text observed=2026-08-07T14:44:26.481418Z digest=sha256:7d6e8da42471caac98addba3c674f2bb3ed2851fa309b247ff759aac1dff67bb

Observation 8185b8d3-6295-4e2e-a530-3c59cd2927fc · outbound

This paper cites Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation.

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Reference 50

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source=pdf_text observed=2026-08-07T14:44:26.633779Z digest=sha256:0cfaad1568a0c6178fafe4889be6ade5340c145ca74d3c4dcfde1d7aabe1a067

Observation 69a2e8ab-2c88-4722-bcb5-184158884a42 · outbound

This paper cites an unresolved cited work.

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Reference 51

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source=pdf_text observed=2026-08-07T14:44:26.731160Z digest=sha256:dd0ff7bb0a6f85d78dfbdc22f9136df53c9806d1ad46a4c0a646ab24868c3baa

Observation 3bb98f6c-2b2b-467c-8b5e-149a61a3faaa · outbound

This paper cites an unresolved cited work.

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Reference 52

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source=pdf_text observed=2026-08-07T14:44:26.812812Z digest=sha256:9c6209565bce476d7572956b34d73fc893174d232aff63d9a1d1ef71122439e5

Observation cb746375-f049-414c-a6ef-9e4f50a47f6e · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 53

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source=pdf_text observed=2026-08-07T14:44:26.949225Z digest=sha256:404553b046734189c880659f395de638ea7978ffab90c315c3e632e468da6980

Observation 19867453-7e49-45c5-aec6-44965de8af43 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 54

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no resolver link, observed 2026-08-07T14:44:27.021816Z

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source=pdf_text observed=2026-08-07T14:44:27.021816Z digest=sha256:a783fe62c846986feee9f674f2ed2fb5acf34ff01591c971b6f26483b73688c6

Observation a27b0095-2a01-4d51-8026-2f05909fef83 · outbound

This paper cites Federated Intelligence: When Large AI Models Meet Federated Fine-Tuning and Collaborative Reasoning at the Network Edge.

Get Experience from Practice: LLM Agents with Record & Replay Federated Intelligence: When Large AI Models Meet Federated Fine-Tuning and Collaborative Reasoning at the Network Edge

Reference 55

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verified exact
local_arxiv, observed 2026-08-07T14:44:33.405295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:44:27.142810Z digest=sha256:faab88eea370966089bd8dd7996d1ce51f65e164ca3a465655d2015651829e08

Observation a2287149-61c6-491e-ab33-e5795d603465 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 56

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source=pdf_text observed=2026-08-07T14:44:27.266489Z digest=sha256:d07aaad5957bec0864dcf2c9355d46376b3d6a9d6e27c7d37d8877cf12d45a6e

Observation a6d3e755-bd33-4607-bc77-743f0360855b · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 57

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source=pdf_text observed=2026-08-07T14:44:27.345119Z digest=sha256:6dc9327d9f3feed611ce4397fc3c9cc938cb34e795390d9168b04b0ddad6c7ac

Observation 7077b278-696b-44e5-9fc9-c73e823b450f · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 58

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source=pdf_text observed=2026-08-07T14:44:27.613927Z digest=sha256:9bcb6fde7cf5ece0b212f29574b7386a73794dae1cc4d35248b2e3d91bfaf687

Observation b92a7833-ad6c-4f4b-bebc-25588f06499c · outbound

This paper cites A Generalist Agent.

Get Experience from Practice: LLM Agents with Record & Replay A Generalist Agent

Reference 59

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no resolver link, observed 2026-08-07T14:44:27.822343Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:44:27.822343Z digest=sha256:509c960418b77b3a0cb05cf1bf101d3fb1e22a8cf908f4cdbb481116024b507a

Observation 7699b73d-2bcb-4537-9c75-d39a5ff35452 · outbound

This paper cites DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition.

Get Experience from Practice: LLM Agents with Record & Replay DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

Reference 60

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no resolver link, observed 2026-08-07T14:44:27.916339Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:44:27.916339Z digest=sha256:52f7ca02808dd6cc46c37abac892e71db983d16f0b897d2d04a2c357bf386b0a

Observation b7b8a427-da5c-4053-aed3-177df5d14bde · outbound

This paper cites A Proposal for Evaluating the Operational Risk for ChatBots based on Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay A Proposal for Evaluating the Operational Risk for ChatBots based on Large Language Models

Reference 61

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T14:44:33.053411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:44:27.742266Z digest=sha256:f7fa85909f254083c334d44c9b9e8d67ba8654dbae0772116f92e909ddca8a3a

Observation 7ddc65b9-8ded-43f0-a0c5-7d6ccfe7e8bb · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 62

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source=pdf_text observed=2026-08-07T14:44:28.138446Z digest=sha256:76322e4381b3830debcd430102baf035d4fb173ca59d508611681bd5608d73ae

Observation 960fdf45-8f3d-4f63-a8de-113ea7627036 · outbound

This paper cites Lee, and Josep Torrellas.

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Reference 63

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source=pdf_text observed=2026-08-07T14:44:28.228407Z digest=sha256:aa7ed10ef96b80d099b25a1740a2390e3500a2f7e81be0e4887bff7cf8a385c9

Observation 39645ccb-d26c-41c5-80ff-275f6bb40070 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 64

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no resolver link, observed 2026-08-07T14:44:28.023920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:28.023920Z digest=sha256:c51ba6a08ad21339eef061acf3d0215a2135a405fe4d07eab3d99f27c24a2cb0

Observation b105c3a5-fa8c-40c6-9513-43e0b16022aa · outbound

This paper cites From Mind to Machine: The Rise of Manus AI as a Fully Autonomous Digital Agent.

Get Experience from Practice: LLM Agents with Record & Replay From Mind to Machine: The Rise of Manus AI as a Fully Autonomous Digital Agent

Reference 65

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source=pdf_text observed=2026-08-07T14:44:28.393229Z digest=sha256:6c02666bda7bfbc912fda306e765867672e90ea1ae622e2aad2e6619035cb150

Observation 3f641d6f-72a4-47da-8750-99b4926d36ed · outbound

This paper cites S-LoRA: Serving Thousands of Concurrent LoRA Adapters.

Get Experience from Practice: LLM Agents with Record & Replay S-LoRA: Serving Thousands of Concurrent LoRA Adapters

Reference 66

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source=pdf_text observed=2026-08-07T14:44:28.529284Z digest=sha256:fed9046bea643d62860d3eb5cda557538884f624869853f8bd5ccbdf10dc221e

Observation fda44509-cab7-43b2-9103-5c371ad06f07 · outbound

This paper cites Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents.

Get Experience from Practice: LLM Agents with Record & Replay Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents

Reference 67

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source=pdf_text observed=2026-08-07T14:44:28.320095Z digest=sha256:7843e2e2ed4ac4a7a3800fdfe0bc92476b6617f594f13d000996d80fc6df7ded

Observation c51d5d75-343e-4cb9-a882-1fa4053f1ed3 · outbound

This paper cites Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG.

Get Experience from Practice: LLM Agents with Record & Replay Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG

Reference 68

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source=pdf_text observed=2026-08-07T14:44:28.742813Z digest=sha256:9fb36e49a2e4052d6e56e9abdddaddfd2c820dffc378f19dce2690477f5b1db6

Observation 60bbecd0-3665-4f43-bff7-cf65d971ceb2 · outbound

This paper cites Can You Mimic Me? Exploring the Use of Android Record & Replay Tools in Debugging.

Get Experience from Practice: LLM Agents with Record & Replay Can You Mimic Me? Exploring the Use of Android Record & Replay Tools in Debugging

Reference 69

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:44:32.468956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:44:28.832097Z digest=sha256:903eeb979ee53800d8943e37eabdb544c784e4c0730da97ae095b7c7c478f1f0

Observation 581bd1e3-da7a-4c84-a7c3-be256775e294 · outbound

This paper cites FlowAgent: Achieving Compliance and Flexibility for Workflow Agents.

Get Experience from Practice: LLM Agents with Record & Replay FlowAgent: Achieving Compliance and Flexibility for Workflow Agents

Reference 70

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no resolver link, observed 2026-08-07T14:44:28.651341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:28.651341Z digest=sha256:93c2ed17efeca5a469537f8f47887f5135eddf086b0975136bd4e4b1ce2a4a98

Observation 6987f857-a898-4891-89bd-816eeb27d00a · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay A Simple and Effective Pruning Approach for Large Language Models

Reference 71

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no resolver link, observed 2026-08-07T14:44:29.040161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.040161Z digest=sha256:9675367a5f2384fbee0e236e908e02dfd047f108d601761174fec36c1c953bac

Observation b91abf6b-71c7-4e8d-bcc3-4c82e5b5459f · outbound

This paper cites Fast-Slow-Thinking: Complex Task Solving with Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay Fast-Slow-Thinking: Complex Task Solving with Large Language Models

Reference 72

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.166622Z digest=sha256:2056dbf4bc26376e650270ad67d74ac4d7c41bf9717fa1f765bbebe196f9da1d

Observation b93cff18-f9c7-4b29-976f-43f12e3e446a · outbound

This paper cites Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 73

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no resolver link, observed 2026-08-07T14:44:28.962167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:28.962167Z digest=sha256:bcffe9ce31ada8edeea787ddd32fe5566ffd01a06f496b9cca12f9b13e345a42

Observation b448936a-2d07-4665-949a-6e70ebc30046 · outbound

This paper cites Gemma 3 Technical Report.

Get Experience from Practice: LLM Agents with Record & Replay Gemma 3 Technical Report

Reference 74

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no resolver link, observed 2026-08-07T14:44:29.458371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.458371Z digest=sha256:ddf774350dadbe88bd35ba65ad57bedd5945cd842d5b72cc9b4698d72243a0d3

Observation 49c4bff2-63cc-4cb6-90c8-0991111fcfef · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 75

Resolution
verified exact
doi, observed 2026-08-07T14:44:31.545999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:44:29.585105Z digest=sha256:bb17b9529c6dbfd0c4ed3b9e14e06e30d98d67f4f18ae0f0cc5e8c89653f0ba8

Observation 5a1c83ae-065e-4477-b412-4df8d725b46b · outbound

This paper cites Equilibrate RLHF: Towards Balancing Helpfulness-Safety Trade-off in Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay Equilibrate RLHF: Towards Balancing Helpfulness-Safety Trade-off in Large Language Models

Reference 76

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no resolver link, observed 2026-08-07T14:44:29.293072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.293072Z digest=sha256:d9e411a5bb1d6e22eaa17c22ed5eaa282bd6ada96a48d70ceab3383d469596bf

Observation 8a4eb285-b48c-484c-acb6-a60cdd51e0b2 · outbound

This paper cites A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment.

Get Experience from Practice: LLM Agents with Record & Replay A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 77

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no resolver link, observed 2026-08-07T14:44:29.819479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.819479Z digest=sha256:22816864dfd4fffeaa16c2ffec0d7d018c8bc466000d795ce2e89fe9ab3d28d0

Observation 26c69b02-4de2-4ea3-a0f2-f3937dc3a5f9 · outbound

This paper cites Tina: Tiny Reasoning Models via LoRA.

Get Experience from Practice: LLM Agents with Record & Replay Tina: Tiny Reasoning Models via LoRA

Reference 78

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Observation 5678a4a2-2ee3-49dd-8166-22031c443bac · outbound

This paper cites BitNet v2: Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs.

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Reference 79

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source=pdf_text observed=2026-08-07T14:44:29.723829Z digest=sha256:2dc7e8a117ed27dea954c554376e22e71744b95d9e4fa48a6e22d783139ddc36

Observation e44114ca-c3bd-48af-953b-2609496cef07 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 80

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source=pdf_text observed=2026-08-07T14:44:30.159597Z digest=sha256:c85e424a00932ad7bd31cffb623ea3d829715da4217d0d2975d840b4580dfa5f

Observation 596e1474-6c0f-410e-b7ad-6b0edabae4fb · outbound

This paper cites Mobile-Agent-E: Self-Evolving Mobile Assistant for Complex Tasks.

Get Experience from Practice: LLM Agents with Record & Replay Mobile-Agent-E: Self-Evolving Mobile Assistant for Complex Tasks

Reference 81

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source=pdf_text observed=2026-08-07T14:44:30.416444Z digest=sha256:e89769acfd8009edf16924da4f7ffecac9d3b510ffb4a7ff0f5f9198321cde9c

Observation ef7ffe5d-29ee-4cb9-a457-ac9f10257f54 · outbound

This paper cites DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution using Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution using Large Language Models

Reference 82

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source=pdf_text observed=2026-08-07T14:44:30.075020Z digest=sha256:9e1bf8bf5e3771b0ef964559115e999a706fdbc8cb76043025c3d62ebeb2090c

Observation d6027c28-87f7-4c77-9cfe-c85e608cc3a0 · outbound

This paper cites Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy.

Get Experience from Practice: LLM Agents with Record & Replay Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy

Reference 83

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local_arxiv, observed 2026-08-07T14:44:32.033083Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:44:30.556770Z digest=sha256:674d5108a0014df452a79cf85db21871bc8a7ebd6deabce24bce61e21eade3a4

Observation 8cbd9611-d375-4820-bb82-4c423f530f30 · outbound

This paper cites Reinforcement Learning for Reasoning in Large Language Models with One Training Example.

Get Experience from Practice: LLM Agents with Record & Replay Reinforcement Learning for Reasoning in Large Language Models with One Training Example

Reference 84

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source=pdf_text observed=2026-08-07T14:44:30.331311Z digest=sha256:6e2b4e45365af8987ff691132bffbc8d198986e5d2b8aecf754edadd51db02e8

Observation e04c5f9c-03e2-470a-bf13-004b482d53c5 · outbound

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

Get Experience from Practice: LLM Agents with Record & Replay ReAct: Synergizing Reasoning and Acting in Language Models

Reference 85

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source=pdf_text observed=2026-08-07T14:44:30.678374Z digest=sha256:ab11bcaf9ce35cac06b84c80f97f01ba665d97f57de5fa3e645fb66fe2dee7d0

Observation ea4ef6c8-cf92-4d34-bb53-3365c52bbbdf · outbound

This paper cites Base Models Beat Aligned Models at Randomness and Creativity.

Get Experience from Practice: LLM Agents with Record & Replay Base Models Beat Aligned Models at Randomness and Creativity

Reference 86

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source=pdf_text observed=2026-08-07T14:44:30.481737Z digest=sha256:e341b7b654a9b5090cd234379d7c125ed75524954f69ee8d210626f63dd376e5

Observation 4bb40898-03fb-41e3-b4b3-2d111ac82ee2 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 87

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source=pdf_text observed=2026-08-07T14:44:30.849701Z digest=sha256:71e78b7eda2a0cffeb49c49f83815aa9a1bbda797be05c02eedbf71c6c831017

Observation ad5221f1-1714-46ad-8076-f4583c2a30da · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

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Reference 88

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source=pdf_text observed=2026-08-07T14:44:30.616295Z digest=sha256:e3719b9c5cce2c82734b3725f96090de02579522149ac666b70118628f6f337e

Observation 0a304c0d-850a-48ab-9d2b-09a464af0328 · outbound

This paper cites Absolute Zero: Reinforced Self-play Reasoning with Zero Data.

Get Experience from Practice: LLM Agents with Record & Replay Absolute Zero: Reinforced Self-play Reasoning with Zero Data

Reference 89

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source=pdf_text observed=2026-08-07T14:44:31.034343Z digest=sha256:f200a324606f7c9ac6de970205fb2205c94522c4ace4acbaa11da632f9e828ae

Observation f4e8ea85-a4ae-4260-a115-d904eeb8d472 · outbound

This paper cites UFO2: The Desktop AgentOS.

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Reference 90

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source=pdf_text observed=2026-08-07T14:44:30.739334Z digest=sha256:d69015a5105463e0bed688992a05b10fe89c7f07070860d5606ac1081adb2ef6

Observation 4e03b32e-bb62-4a96-8b4f-4b971aa5d7b3 · outbound

This paper cites An Empirical Study of Qwen3 Quantization.

Get Experience from Practice: LLM Agents with Record & Replay An Empirical Study of Qwen3 Quantization

Reference 91

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source=pdf_text observed=2026-08-07T14:44:31.192511Z digest=sha256:36bc63503c348f35a03e435e5c901d94f9503405e0643e1cd900ba805ece734f

Observation 8d17247a-c8c3-40db-8060-ac69da1d7cc4 · outbound

This paper cites Explore, Select, Derive, and Recall: Augmenting LLM with Human-like Memory for Mobile Task Automation.

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Reference 92

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source=pdf_text observed=2026-08-07T14:44:30.927136Z digest=sha256:e9e122e19add97ac70e0863ccd66073baac237f352dc9a1fa1bf1807aeff3f1b

Observation 73ce5631-804b-42e7-a0dc-7ac9d5f4e945 · outbound

This paper cites SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks.

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Reference 93

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source=pdf_text observed=2026-08-07T14:44:31.351435Z digest=sha256:046a87f92837cfcf4ded3e6a5893a7a527b97ba7ffec85f2bff7db98b7e5bfb5

Observation c16780d9-72dd-4c6a-9e28-2a1b35d56b2e · outbound

This paper cites Improving Large Language Model Planning with Action Sequence Similarity.

Get Experience from Practice: LLM Agents with Record & Replay Improving Large Language Model Planning with Action Sequence Similarity

Reference 94

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source=pdf_text observed=2026-08-07T14:44:31.124698Z digest=sha256:00712dd1cac3a567e1efa19fbc315f38779204281590475f04f828b525c87097

Observation 2f305c83-0623-425e-b549-0eea3ae05b31 · outbound

This paper cites Agents: An Open-source Framework for Autonomous Language Agents.

Get Experience from Practice: LLM Agents with Record & Replay Agents: An Open-source Framework for Autonomous Language Agents

Reference 96

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source=pdf_text observed=2026-08-07T14:44:31.254713Z digest=sha256:98c67884ce3cc679652027ae9f9aa5336b1af826edc73194a2ca1fd860632d9a

Observation 45cdec95-7520-4ad4-9f20-e75956f887dc · outbound

This paper cites InProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (Denver, CO, USA)(SC ’23).

Get Experience from Practice: LLM Agents with Record & Replay InProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (Denver, CO, USA)(SC ’23)

Reference 2023

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source=pdf_text observed=2026-08-07T14:44:27.442200Z digest=sha256:b8e54b9206fce1e6a48a45d46698f6de9178b5351b3d890a07bd74161bb9963e

Observation 4ce21b4e-fdd7-4e9b-98f7-45ca3d661dbe · outbound

This paper cites Sleep-time Compute: Beyond Inference Scaling at Test-time.

Get Experience from Practice: LLM Agents with Record & Replay Sleep-time Compute: Beyond Inference Scaling at Test-time

Reference 2025

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source=pdf_text observed=2026-08-07T14:44:26.092102Z digest=sha256:e0022164604d2d1eb19e34a282aab9a141c552ce8488ddddd26978c72ee3c6f2

Pith citing papers

Observation a68f3fd5-d5fe-40c7-833d-244c3b1f8a82 · inbound

A Survey of Context Engineering for Large Language Models cites this paper.

A Survey of Context Engineering for Large Language Models Get Experience from Practice: LLM Agents with Record & Replay

Reference 281

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arxiv_id, observed 2026-05-13T20:58:45.497878Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T20:58:45.060041Z digest=sha256:207b7c715ce13135770b380dd3abce9bbf86299594b6eb00826baaaa07de91e6

Observation af5c258c-12db-4046-9a0b-41756ddf2f45 · inbound

MobiAgent: A Systematic Framework for Customizable Mobile Agents cites this paper.

MobiAgent: A Systematic Framework for Customizable Mobile Agents Get Experience from Practice: LLM Agents with Record & Replay

Reference 6

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no resolver link, observed 2026-08-05T13:34:58.922731Z

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source=pdf_text observed=2026-08-05T13:34:58.922731Z digest=sha256:4cc1dc9488bf24cec25cd98d38d80b08d023645242b3a28b27d9cd578e484f54

Observation 3a5cc48d-7dc9-4d87-8493-617c7b650ea3 · inbound

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory cites this paper.

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory Get Experience from Practice: LLM Agents with Record & Replay

Reference 10

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verified exact
arxiv_id, observed 2026-05-19T16:47:40.526261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T16:43:37.472644Z digest=sha256:f8887d8f1f2c2dfc9a0a9da2f626fe7a89289baf33151c8cee73eef4452c4673

Observation 72cbed0f-8284-4978-8133-62196e3302b1 · inbound

Trust Region On-Policy Distillation cites this paper.

Trust Region On-Policy Distillation Get Experience from Practice: LLM Agents with Record & Replay

Reference 264

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arxiv_id, observed 2026-07-01T20:56:13.645618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T17:38:50.313305Z digest=sha256:68612ef1f30095168f094cb8ee8ed278ad36451448527b51e918484202bca468

Observation db5d8fc0-97db-4219-bac5-83eedb5ecc7a · inbound

PreAct: Computer-Using Agents that Get Faster on Repeated Tasks cites this paper.

PreAct: Computer-Using Agents that Get Faster on Repeated Tasks Get Experience from Practice: LLM Agents with Record & Replay

Reference 11

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arxiv_id, observed 2026-07-03T20:58:57.422347Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T01:06:26.643487Z digest=sha256:09674379b56e081e48e0be91301f1b4ca071bfc3a8ac4d2a008e2e6ac885a026

Observation 0568d08b-d9df-48df-ab78-090ab505c765 · inbound

HippoSpark: An On-Demand Experience System for LLM Reasoning cites this paper.

HippoSpark: An On-Demand Experience System for LLM Reasoning Get Experience from Practice: LLM Agents with Record & Replay

Reference 4

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verified exact
arxiv_id, observed 2026-06-30T06:54:21.398181Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T06:24:47.449777Z digest=sha256:38624f514879be963a35f0296105c50a90868858b263876bc64846c02971a91d

Observation a5c8b527-a7d1-4699-85bd-4988962d4dcd · inbound

Industrial Practice of LLM-Based Test Case Carving and Assertion Generation (Experience Paper) cites this paper.

Industrial Practice of LLM-Based Test Case Carving and Assertion Generation (Experience Paper) Get Experience from Practice: LLM Agents with Record & Replay

Reference 14

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source=pdf_text observed=2026-07-31T23:23:44.635925Z digest=sha256:266f56ad9afbf8936a9ede6b14a69111223f11aee85f1ac8e632b64b3225a524

Observation 6349fc9a-ae93-49e1-ba0f-dcbb0193d5c9 · inbound

Industrial Practice of LLM-Based Test Case Carving and Assertion Generation (Experience Paper) cites this paper.

Industrial Practice of LLM-Based Test Case Carving and Assertion Generation (Experience Paper) Get Experience from Practice: LLM Agents with Record & Replay

Reference 14

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no resolver link, observed 2026-08-04T01:34:38.984471Z

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source=pdf_text observed=2026-08-04T01:34:38.984471Z digest=sha256:790aa65bf83b7ea42b541c171fe60e27442dc23c7352d2eb088f83b3ce4252c5