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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-08T06:32:00.761636+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:bc4881b544845337e11d4e12ebc935bb401b512f40b33dfefa2845dc2b98eb49

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=sha256:2ab72901fbfd4cbaf5e86f8d0bca1994cbc03aa6e656546da918a4ecc8bd02bd

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=sha256:76c51e4081da1ae8cfca7ee612d04d48fa35a264703a7e60451f76c0ec3526a1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:30.966616Z digest=sha256:0f8bccc877e8e0031b2ac41f8679376bd7c5411d15cede8ea43dfd66ca546ea0

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.136846Z digest=sha256:5928e7bf828591aa0213c06a882661edeca34805ebe35ab77a670202b007d629

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.248344Z digest=sha256:4379bfba80fe02861e43650a1d72131ea60a29e29c76fc96c359d4fdd10f4c94

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=sha256:5c4394471249d5ce95d3d5767b5b4a96e44732588f023c09ee7032b22d6c1c11

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.404344Z digest=sha256:8a2ec98d3ec26d8b789afb7d7891e2df7191c08c06531e819bdcd548e9b07f63

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.494234Z digest=sha256:6d7bbef7954489575ca8d73204fe0ec0940b492e578f8ee311ad845b07f0e5c7

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=sha256:4619fa94f95920ea311a7214a610dea033c674fe25d56862a727b11e317d3de6

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=sha256:03b7d9b9644f25bdb5fae7d9b708bb999fa5a95922c3fccc3ba9efa250f79f3e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.795678Z digest=sha256:b8ab0d323289b420cec6d10a2a8b1a054c54a9ccede119eb51c4682d5633ea1e

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:c6107006363f7877c39961847daae15da952daba7b40b1fecd6499445f0dd3ef

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.879288Z digest=sha256:2451f0e31beb46971d1b38838f4b2aeb7626718db88e0e3336f3c0a346dcf7f5

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=sha256:9d9bf4c497e3bf3f6cc503e28ca3c9d5dc331dfe428943eb2e818493264b9766

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.886448Z digest=sha256:803688ef05989c5ae7773732941b6281683aa0e025d03ac3067c2c1573673f93

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.889828Z digest=sha256:3a5a74038d63bb4dc5131e9bec1bf5dd73dec63220e0267a781c80cc9edee677

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.893618Z digest=sha256:1d1a6749ff47f02687df0654ca26662658a02ee6fa1001055fa31974273bc4fd

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:34:31.897424Z digest=sha256:3a7309216c533cc7d2a7dc78d921fa9af778cd252a59efd8ac39035c1e51accf

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:ec46ec26598e3621724c5535bfa343805cc90ae23a56445e525e1bd7e2e27eb5

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=sha256:6eace8e140b015a4dcbb77ff67b090fc93e1eca0981b7287252cf3c006788943

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=sha256:7cb60f34c7dec24a065f7dde5fe7eff72ee201c8f24435490c96ef2d52a7ce25

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:11:29.183856Z digest=sha256:89594f033442d4eacdb3b60eac230a6c4dcba0cd99d51f5ac53fc1901aaa66dd