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Paper Citation Record · LEDGER

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As of 19 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 2026-08-19T06:32:44.657259+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:bd973317174024ca845abd567a87102e4999a2b0213a907c29e505a3e97de04b

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=sha256:11d8ffc51202be3a171a0b15836e35ecb6a389a699ec92dab5d80dc2dca5eee3

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=sha256:5f4abd479794eeb582f5e87bc431b982a4bb4db7fcc91b4576fe48b427e8343e

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=sha256:8b5d67f34f34c3bace0e8b4c9f57363f275c095cf0dd5c503fcde4ee6afc7122

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=sha256:53a568c3dc099b6c2ee44f9f5a1bad546838794cb9e272c3af1ad96bf1f4cb43

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:b6d8689b06589655f31322e8062d9e66deb759e6067d9f0a92298722bf8ed6c1

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:b0da1896c9b007b7e6ddbe50edb555f9358a05961883168696cfaeb3503da434

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=sha256:70387200aa6bb7d37356eb7301f61d9a6216d7ad8e42e587e7777e92b2e43bf1

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:a7b75e1814d78d81afb8fa5e3a21eb62ad55c5a7e76ea09a223be77e19acde7d

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=sha256:8fa95ee1db9b168e3d9e9beb2e056684bdb04e0a5d6b95240e2468d650272571

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=sha256:6a6bb29ad94073b96c4e048616c1681d3c6bb7787dad5d0fca4e5490d3fc61fd

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=sha256:9e3d8ce47038fc6790cb38037bcce053ef02ccbbd007f5f8ba3e9b5f5c3be508

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:d9e199660c56bc365cc89a562dca4e63bb136c83eba2e1e30b96eb5939bb7781

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=sha256:9d907c5b1548820292d6218c3523aa68716f9e8cf50a12827b9aa20f846e3368

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=sha256:83eff54a27bb951869bcfee2418d477330e02cd6dadb4ba036874e31bcc74801

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:d90dc50be80e00be3456d89917a5a096b18b4a222b3a964bbcffff66e4444748

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:d5e9f52291279d722a407a5e644b1d66b4e9721a7b3c2b7da9cf86ada4271c4e

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=sha256:60a3b0d412bb48bfabc0ffb324654c9f31848a8cd890504667a9aa43eb0cf2d6

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=sha256:15e85d7db8fd52713f61730a38f41ac7214c36d8f7f71b8fe105b16c79961044

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T14:44:23.216049Z digest=sha256:d1eb4837a087824f7509af1b16ca5ff87dc9e342c2caf0452fe3ac67b2a2bb5e

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:edfca3d01b9da1bc0325d0c50c6b5308033dd56bfede0b6fa8687afa470c9525

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=sha256:1b799d81679887783056ce76d2ade234cffd8c6290917720591ad33961016ef5

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:cc4f69bf0e9018a00fa2a4387b0426e7a814247fa22401a615b39c9467a6ede0

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

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

Get Experience from Practice: LLM Agents with Record & Replay Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use

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:e0385adb96fe86d4de0f6f3b5753b2c4240bf5939d279bcd931732c75de359a0

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=sha256:47ce8661978f4b4a42ea1573ed25e253c92c85b4fefc4819b09938a287a19085

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=sha256:42d51ec32011fc278796eaba95395a1183c5beb823937ab369deff8ec0222bef

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=sha256:17efb9feed22294997f7bd9a23f15f8231ea02fa878a41d3078f95f9e468df9c

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=sha256:2a24cbfb05bd7441359e3d8d0d8e1bfb090335f8af705ae4dfb518e06f7218d7

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:a5d224e64f61f52098f274ac4c1e673cca1f45afadb46326890ad43f39bd1a2b

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:f50f980500557455b9dd0f8d75b454fc9d67d7375af9b2565a8505eb110259ad

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=sha256:86257c0731434d944fc4492e2df9a32bb133eb80a5d62ecbe24f275ba339f3e3

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=sha256:19200bd15e8dd4c570bda9085e99a1fe0af4b95ad072291708243518e3b53a87

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=sha256:562fcdce7599636a63169269b95b907d4f758a3edafac7b39d07225c9ac86c3a

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=sha256:2fd6c7ba9308d204f7040c7a09c11f4df2d94f423f90010c0b8244e5b6c802a8

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=sha256:16156c633ad7fa97da1185e3c55a64dbfb663771fd4686f31a5039b4d5e7cceb

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:c6c364bdc3d86c91bb7d6d23f22937743958f46dfc23fec6bf416d3614502ffe

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=sha256:0375fec1fbb68220a029b77af95b743bacc644e8ed2fa7dbdd5e8cf41d883366

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:a9e9194a9083bfb10b7d6c5ca9183a325a16868d678267a8d01d22efb101ca53

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:a0fffb6c6f36839cefcf5fe2309d4e269ea4d6419bbfda300ec628846aa1050e

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:e805deefc781910e4978a6e6ddc767a8e891281d4d03264a364212ee765a36b0

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:ddab42458eff86f3464bacd9c5b8dbef6d5b9f2a149909e09cb9e1324cc8d09f

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

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

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Reference 42

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source=pdf_text observed=2026-08-07T14:44:25.389219Z digest=sha256:385b4a7eb98500fa967dbbc942c01d3ca7b4058ae0dd7e637018a8493648c513

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:e805c5c678235375ecb03f0f9a722137bf5e405dbc50698592d2f5b97d0d0877

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:c3a793d0ee5c30bcdb6e666416f98d6723817a69bc224ae7d7cd76600e0edd6f

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=sha256:185fb3a2f431dfe07f680511a757e07a058ee5591d3f2cb5a7ed28d45bf6ad06

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

This paper cites Gonzalez.

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Reference 46

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source=pdf_text observed=2026-08-07T14:44:25.908238Z digest=sha256:74c7174863fe7db3a6f109305c8c1b3e45ab8a64c9cf155c784a46b2c7316093

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=sha256:1cbaf6dea023f17ff44e2a1cf2975921689a1ff939a394afd087a4b2090137e4

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=sha256:34daf03f815b80c1a4e0f892b2d094ce1d019a3123a7330ffca0a81ed5e0146d

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:eb7d847a6d868d271bdfbe585f1d03b74481f36e1322e72ed26d9bc1806d30c9

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=sha256:1f65351f33c2668d124917e18a5a85a37b19be518ea6cb30857358ba8c2a6d7b

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:dec7679f5583ba79bf1a211235c9ebeae69f55757c634c8cb67939947537a268

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:a8647dd2a8121b2af5c255718ef9fd05eaded22ba3ab1f092ea6468a966b3c7b

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=sha256:8c4fa19417603f3855e274d6b9982e542046882402e7287b3c54f1359a0350f9

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:c809dda3fe673d1867ad49584c6143307a274ab4fb798ea690eccdb3a31c964d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T14:44:27.142810Z digest=sha256:999e15098144b8886c2e534747d55d9a7dbd4180deb922163bd152edfeb9f23b

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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no resolver link, observed 2026-08-07T14:44:27.266489Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:44:27.266489Z digest=sha256:a8cbd453a011a0bc29f800f657e558f8ee6a003446ea6b0ea7108a559ef69d19

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:c366ecde27363a1d8edc3f642ddf1d5c83829d8ef8b0c19a0e476a19be0ca01f

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=sha256:6de9eb23d0c5deb9260b201947c12463ae4dd3c6ce458f26afa485bba16de3fd

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

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source=pdf_text observed=2026-08-07T14:44:27.822343Z digest=sha256:36926fe0b4e1049c439ea838047abcd861ff27194e610566ce4a4346c499d6c6

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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source=pdf_text observed=2026-08-07T14:44:27.916339Z digest=sha256:47ec6db712481c75492163855148d5ee283ba6753e8ca76503562330044ae740

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T14:44:27.742266Z digest=sha256:d5871bec09f59ac83e1322ccf8ea89399c1c973201c9cd4e8346f5838b012919

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:e76624c2683d232d24f6b602473a0171acd63d301d47f72073a26efa97d4bd91

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=sha256:01c2c4577c0662665b69b3cd4f7763d00967e1dc5dd12303e61cae9023a0b3d6

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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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:44:28.023920Z digest=sha256:74097dea95d790602f3cc806a76a95df150d5ea4d3c3d0f85c9f4a3578259156

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=sha256:1848ad25bb1e3e07a83fa72b6648a35474d3fd662abd9c11027c361efcd85b85

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:b7d20c7fad2028625affbba56a64f3de21bec05211d4d042805fbfeeb3a96875

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=sha256:99e45d92e32ded8b332d6c35adce87502f0a12c7e98449c17a9d85d10b651f62

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=sha256:49ed94864db7ac8330dedc0aef37d30dd2d76a91dc12118ade64fea87cf03ad1

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T14:44:28.832097Z digest=sha256:d9cc75959a690ecdedb61596f4bb3d0319ab28a698d61a14b5b187595e08b1a9

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:c265ea92cc0ca08fa6a5dfede388de33ec9f57f00b77a4cb602c7de457beb64d

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=sha256:4554ebf5f0eed8bf2204e1a45a6ef374405adb654058d1dc2fc475ad74563068

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

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source=pdf_text observed=2026-08-07T14:44:29.166622Z digest=sha256:a38f7e8b2a075dd83f5d252e413dbe97d68f1d0befa5116aae965d9f943d89c0

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:28.962167Z digest=sha256:fa0a707371e1e47e771d4646892146b780fb29a97780c5088aa785303def72d3

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:f4699b2fa41270106eb8b02fc1247f370d792f9659e6f9254e5413379cd2c898

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T14:44:29.585105Z digest=sha256:85980b0ade2c38d82adfa1a2b6c328a0f90d2cd2deb9e4e58a3b11fbd561b842

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.293072Z digest=sha256:1d9cd4f58a2c19d2449b7f32397491ceedda50695f2499e569ad5a1cb4a80c8f

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=sha256:632acebee9cef96b5794cd5b6f930ed3f37e2877aa3f0b1111232219451c4ecf

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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source=pdf_text observed=2026-08-07T14:44:29.928994Z digest=sha256:efce87cf2a2e32d445b5a23bd7ad554edbe1af30fd2bb47a4768d9b086ecf47f

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

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

Get Experience from Practice: LLM Agents with Record & Replay BitNet v2: Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs

Reference 79

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source=pdf_text observed=2026-08-07T14:44:29.723829Z digest=sha256:1fc8158602409ca3b42adc5f7b8348600bf9f322f9dfc21d9abe410fde8338db

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=sha256:8a9f50cd38b04e05317f54f5d4ff8ec98e911e89fae0001552e363c4f66acea9

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:e9cf802fa130fe379d4db74f9817c7dcf488899af67bfe43ce1816e721ee10e0

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=sha256:6b79a33b199ea1634f28348aa340e0766f4d52f42c9efb9343f0dcd11898aa52

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T14:44:30.556770Z digest=sha256:4c9f4e848b8182b642734726ff7411410041c3a1cf49b2a780af7d24573a78ed

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=sha256:39140b004fe7e4ca4ab3c206b2aec339205d2d49049d893beefdf242f261f012

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=sha256:410949956e13f23edfdd383755025d0f57fa728f60028a67edd15ce8e3a044ca

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:f439522106f548b878ad9bd90bba02ae799b37f92a5bf71882267eec904fc4e3

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=sha256:7f7c1964a01f0eb9d3743d9123f026d477f0d93c48bcf2d1419a831191eb8021

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

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

Get Experience from Practice: LLM Agents with Record & Replay Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 88

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no resolver link, observed 2026-08-07T14:44:30.616295Z

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source=pdf_text observed=2026-08-07T14:44:30.616295Z digest=sha256:a8865c5c23ce98f6f87bc320871f37b1d6aa9c56f5e4a12c559aa3cbd9fb7ed2

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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no resolver link, observed 2026-08-07T14:44:31.034343Z

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source=pdf_text observed=2026-08-07T14:44:31.034343Z digest=sha256:f0f48fa15ae6a8fbdbc6f48f876fba38341285e5d038775062d647db19761979

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

This paper cites UFO2: The Desktop AgentOS.

Get Experience from Practice: LLM Agents with Record & Replay UFO2: The Desktop AgentOS

Reference 90

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no resolver link, observed 2026-08-07T14:44:30.739334Z

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source=pdf_text observed=2026-08-07T14:44:30.739334Z digest=sha256:011ce1f047fee1f3a24dbdee49af3faa440a22c9bbf37b8f71fcc8492d55740f

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:e7cbac1644996f8a844af14492f5ac47ea483b61f143918872ebea3aef3121b9

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.

Get Experience from Practice: LLM Agents with Record & Replay Explore, Select, Derive, and Recall: Augmenting LLM with Human-like Memory for Mobile Task Automation

Reference 92

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no resolver link, observed 2026-08-07T14:44:30.927136Z

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source=pdf_text observed=2026-08-07T14:44:30.927136Z digest=sha256:a2f361de6f1cc4a4093fffae3be85be457d2f0c6946ed12b8c29ca24de616b46

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

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

Get Experience from Practice: LLM Agents with Record & Replay SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks

Reference 93

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source=pdf_text observed=2026-08-07T14:44:31.351435Z digest=sha256:08309d7d0db7efe35f517147571e07792f5a19179470faf8cae4b5366fd7561c

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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no resolver link, observed 2026-08-07T14:44:31.124698Z

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source=pdf_text observed=2026-08-07T14:44:31.124698Z digest=sha256:ff7fede82d36f8e93d7035bbb12a7aecf355290ab7449d1862a72aa83f841bf0

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=sha256:3b31873620930c6982ec37709363d9079192d5ef1ff0f859f895acb3ca9855ec

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:e6708e07a9da0d5802e3bc54bff0cf4e56a6c3bba3267d7a1ecb804e9210b105

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:d2f791d4db7d6da91ec6d223edf8150e3af65d70e323b19de76b101700804fc5

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-13T20:58:45.060041Z digest=sha256:255356579135b4ba34137affdbcdd672811c89f23b13f305cdbafa6a298dbad6

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:34:58.922731Z digest=sha256:8b020ee0b77fe58f96f0ccddc5aa467216c217c5be391fce727703b2a836c99c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-19T16:43:37.472644Z digest=sha256:8f0ff00836862206ce09c1ac7a5bc944d5b7a78154e997ad93bf20821c9a892f

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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metadata mismatch
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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-28T17:38:50.313305Z digest=sha256:bbd74d90db01a527712cbaeeb0673d5244daa1fd2ee1d0cb13e4063310ff18b7

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T01:06:26.643487Z digest=sha256:ae96a5f90967e84f0cd24de1d5fba2a68f4a1184096cac03413a1b93b43a73df

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-30T06:24:47.449777Z digest=sha256:5d9e64c049724e78d4a539395ee8be73eecfb76010204654ca4b2f052af7c360

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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unresolved
no resolver link, observed 2026-07-31T23:23:44.635925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:23:44.635925Z digest=sha256:ea92d5c3f985159663807b11607a67c6e819264c574d3797a90be6aea55387c7

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

Resolution
unresolved
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=sha256:724cf75e28504c41cc60296571575516c60c08c8000653c6fa716add2b3f162c