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Paper Citation Record · LEDGER

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents

As of 18 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 2 inbound Pith citation observations for arXiv:2505.21534.

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

pith.paper-citation-record.v1
2505.21534 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:34:31.905400Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:45:12.589474Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:11:29.584467Z

Reference resolution

21 of 21 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4e016c5f-50a3-41fd-b21f-7f5892933650 · outbound

This paper cites Accelerating drug discovery with artificial: a whole-lab orchestration and scheduling system for self-driving labs, 2025.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Accelerating drug discovery with artificial: a whole-lab orchestration and scheduling system for self-driving labs, 2025

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:30.606115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:30.606115Z digest=sha256:f1747a2eed6cccc9b2e3a9e621b187e9a0e398e12c9de6d5116311c7905297dd

Observation ecf2a08b-6251-4ac6-902f-6b2c0ef10fd4 · outbound

This paper cites ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:30.696665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:30.696665Z digest=sha256:d0a534df973b29b85b1fcfe0e262a53457fb25aef7c25bc544924b0793fabc58

Observation 54efe15a-4422-4773-b352-f3eb9081fb93 · outbound

This paper cites ProteinGPT: Multimodal LLM for Protein Property Prediction and Structure Understanding.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents ProteinGPT: Multimodal LLM for Protein Property Prediction and Structure Understanding

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:30.796798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:30.796798Z digest=sha256:68006e870a18b39e62acf1311d505bc2d9f6e76dd14496a12d1de136df5188bb

Observation ef8a3f6c-c0f7-44da-aae2-821d0e76966e · outbound

This paper cites Contessoto, Yao Fehlis, Nicolas Mayala, and José N.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Contessoto, Yao Fehlis, Nicolas Mayala, and José N

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:32.143149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:30.966616Z digest=sha256:89abb13dd9c8565bcd4abb9b107f25068fb4f154c939ebfde2fe9435d4a3efeb

Observation 54e25d4a-4a79-4cc8-a5e3-6efec8c07f7a · outbound

This paper cites Reactgpt: Understanding of chemical reactions via in-context tuning.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Reactgpt: Understanding of chemical reactions via in-context tuning

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:32.130195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.136846Z digest=sha256:0fe537e85f3a04f86e3e6e49a9992ad11d1d0b841a0171640f8004e5670e6e20

Observation 651a9b51-7a64-4949-9279-59d4422a7234 · outbound

This paper cites A call for caution in the era of ai-accelerated materials science.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents A call for caution in the era of ai-accelerated materials science

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:32.117360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.248344Z digest=sha256:aa9402b2d4026e302d5e08ccb0bf2dab8d86a017796e2c7aa712b0daaca95ca2

Observation 9b41070b-7fc6-4413-a6d4-9835545bdc9e · outbound

This paper cites MatterChat: A Multi-Modal LLM for Material Science.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents MatterChat: A Multi-Modal LLM for Material Science

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:31.360826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:31.360826Z digest=sha256:517dcd861902859aeab9b8f5f4b332e0a3501a07ec3466907f97b6bec1558db1

Observation b88d3089-37d3-464c-8204-369789467fe9 · outbound

This paper cites Evaluating the performance and robustness of llms in materials science q&a and property predictions, 2025.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Evaluating the performance and robustness of llms in materials science q&a and property predictions, 2025

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:32.105235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.404344Z digest=sha256:e6c81062b2ec00279c5265cf7a519ae08c8d176244378ae7abd5b9e272a5802b

Observation a5be56ad-d414-4228-884f-caf35f53bd81 · outbound

This paper cites Chemformer: a pre-trained transformer for computational chemistry.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Chemformer: a pre-trained transformer for computational chemistry

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:32.091901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.494234Z digest=sha256:4c08615e20d215747283f8ae58a211966458f77dd4e5d83d503f042dc8a6a803

Observation d8f914a3-b408-4f62-aacb-764fc9179521 · outbound

This paper cites Biogpt: generative pre-trained transformer for biomedical text generation and mining.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Biogpt: generative pre-trained transformer for biomedical text generation and mining

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:31.602844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:31.602844Z digest=sha256:dfd735af1aa28ecbc438cd104b2b49c68e48efe721b5d465af87952a46edc479

Observation d7a78607-a19b-4ebd-92a6-560568381ff3 · outbound

This paper cites LLM Agent Swarm for Hypothesis-Driven Drug Discovery.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents LLM Agent Swarm for Hypothesis-Driven Drug Discovery

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:31.785572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:31.785572Z digest=sha256:0d22bf62b6b1c415c3937db49a83a13358e0a411080b21817c809ba63b169140

Observation a08e4e61-8a36-4cc8-8aa7-ca014e42a46d · outbound

This paper cites Generating novel leads for drug discovery using llms with logical feedback.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Generating novel leads for drug discovery using llms with logical feedback

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:32.074349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.795678Z digest=sha256:6c5b7de0cf2c42f1bcd4bbd6b498755a75b34f7b5751c72d9b697f3636f269db

Observation b5fc6a08-245e-414d-a405-93cf8532467f · outbound

This paper cites Self-driving laboratories for chemistry and materials science.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Self-driving laboratories for chemistry and materials science

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:31.875726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:31.875726Z digest=sha256:e31584a10bdfb5f4a9420c5a90877c8457e567db62a6c101c95e65bf472c3547

Observation a20ef0da-d3fb-4b16-ad16-fbe8dea3c4c1 · outbound

This paper cites The future of self-driving laboratories: from human in the loop interactive ai to gamification.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents The future of self-driving laboratories: from human in the loop interactive ai to gamification

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:32.055460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.879288Z digest=sha256:1c5acc5fc0282f66929c8b128e24b88d449a4a15bb7935e816ad47ae94ccde59

Observation d3c7e039-8489-4d1d-9853-6db6f8c24d9e · outbound

This paper cites The rise of self-driving labs in chemical and materials sciences.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents The rise of self-driving labs in chemical and materials sciences

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:31.883012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:31.883012Z digest=sha256:0d55db93373975b2bf878bcbc52a14edd418404dc3d57ed7ef0c4577fc873a4a

Observation 073ce43a-0f47-4f6a-b772-4d26260f9e3d · outbound

This paper cites an unresolved cited work.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:34:32.036395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.886448Z digest=sha256:8eda8dca7a136d9f1aa9566ae18e38dd2036a701c936326449e658f90c344675

Observation 8b166236-0f28-431a-b39d-037fa6c46112 · outbound

This paper cites Drugagent: Multi-agent large language model-based reasoning for drug-target interaction prediction.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Drugagent: Multi-agent large language model-based reasoning for drug-target interaction prediction

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:32.024623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.889828Z digest=sha256:e5223b397e94262d0f877bd519b266453d62dde421cc2afbb1cdf0d7ca840af1

Observation 813ff731-bd1d-4b55-80ea-2b13af25b541 · outbound

This paper cites Protchat: An ai multi-agent for automated protein analysis leveraging gpt-4 and protein language model.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Protchat: An ai multi-agent for automated protein analysis leveraging gpt-4 and protein language model

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:32.012195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.893618Z digest=sha256:2fd0ad8133fb243d53c5ebfb51a1bcf5be2e8fb15631a31f75489d4e9ae1109d

Observation 05c67028-412e-4db1-bab6-5512a7569b95 · outbound

This paper cites an unresolved cited work.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:34:31.997464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T14:34:31.897424Z digest=sha256:3ea9b35f435e0e34388918d762e73137a36fd6f1326dfecc6bcc7372ea783e35

Observation 4c282814-e190-48ec-8b74-8c8040758382 · outbound

This paper cites Agent Laboratory: Using LLM Agents as Research Assistants.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents Agent Laboratory: Using LLM Agents as Research Assistants

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:31.901273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:31.901273Z digest=sha256:df22fd3b56abf2a51910580f41b3f3e969ef33b24646f0286fb94605c50f5752

Observation b30f1b3c-3ce8-4ec8-a0f1-1b457125ee58 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:31.905400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:31.905400Z digest=sha256:d2d9b903e0a7e8e2e29aa173b0e05dde2b0a761cba9594bf18edce09e406a703

Pith citing papers

Observation 7378fd7f-bc23-497a-adf1-9d7645f9980b · inbound

AI4Research: A Survey of Artificial Intelligence for Scientific Research cites this paper.

AI4Research: A Survey of Artificial Intelligence for Scientific Research Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents

Reference 200

Resolution
unresolved
no resolver link, observed 2026-08-06T20:45:12.589474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:45:12.589474Z digest=sha256:500462ef29acfd556a4ac4e2cd8edeea46fadfdbdd497606bb51a01578bfcbce

Observation 686fefd1-f1a1-4150-aeb9-da6a956a7488 · inbound

Technical Implementation of Tippy: Multi-Agent Architecture and System Design for Drug Discovery Laboratory Automation cites this paper.

Technical Implementation of Tippy: Multi-Agent Architecture and System Design for Drug Discovery Laboratory Automation Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:11:29.704199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T16:11:29.183856Z digest=sha256:c6119457cf689702edeeab1a6e991fb81956726eb470888a4ac7e4fe53e566b6