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Paper Citation Record · LEDGER

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

As of 10 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 2026-08-09T06:31:02.800959+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:daf959ee0bcbf0cdd05347f22471266529321d71cd16b87eb42f966eb6b89527

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=sha256:8b1092a24097cd2d0fce3fe8743f61f5a418930d91790303353bac6a8e5899d9

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=sha256:1e4fb4f282b07dfc40762218fca9c424516bb4801822215b9f06fec1aeafb0e4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:30.966616Z digest=sha256:d92a6c442d93d0ae0bd03fae0e024f4d54e60031eecf311ca43c8524c66b85ac

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.136846Z digest=sha256:961ce51592b6f9cc76465ad25e0fb61dd1ba900401a3d979511ef70305abeea7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.248344Z digest=sha256:f0f0cd71d25be253cb8e640ad1f0a47430e9a8a7772db8e8ef861bcfc2da7723

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=sha256:4d915452992e0395543229ab2dee8c84bbf89727395da77c272758393ada1801

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.404344Z digest=sha256:413c0130cc3a81febff54e14bdfc7ac3ab2d85c8bdb2178fb89a1d750441854e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.494234Z digest=sha256:e725b56a64bfb5d6d9bd6a55b13370b7aed60b6dbc8e3149336d5fdad953d39e

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=sha256:51312e3ddcd382c254fd6876c121232fefd29af506b5caa20ec9c3bd054a9259

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=sha256:4fb2609ee5187118f1c05799b5630307730ec21fa56e394d9c1d9911742eb5ce

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.795678Z digest=sha256:e7ac5e489f1945e45b7fe087402294d3347f6710991a1e65a5febd6ee5b2dc2a

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:ac7adbb907ecc09e59fd6bc60ead3d0585daf72e5719e682c3ea8c19b577a87e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.879288Z digest=sha256:d9beeb4df6ad35bbf43114b6b4612d61bf38dcddd22876f848a398d548398728

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=sha256:5b155eba2cd4c348bf36627b430d84414f897d1dc99b78cf1d6ea7e017101af6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.886448Z digest=sha256:2179c18f8f533e6f5ff2a8ac40759d6f4b16aa9cfc0bfbeb7eaca01841b9923e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.889828Z digest=sha256:ec75ceec9e9b25feccdd98cac7859e00cf59e94449b3747e00cd2f5fba9d192f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.893618Z digest=sha256:522359d2c7eb2a33f5073e5a537d773100022e126a4df301939b3573feac5eb9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:34:31.897424Z digest=sha256:d9007bfcf5511204382765b9a46c4bab519832463d3f9258df4445864d272768

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=sha256:12b6e3c27754e66c6a9eab250c43c646f0e850fedca90f8b5ccd6a5c61357b32

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=sha256:55538b6b1b9815f32f7b1540c28689060f6b311324613d1d7ec4eb6be264eeac

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:c21c78cba89ddc25d298e29081dc9d1e3ce880bdeeb89398548aba2317c0d0d2

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:11:29.183856Z digest=sha256:d3d370b7cb00c4554b583aead046ba2fffbb6fcf553d39a71556f37e073e1794