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Paper Citation Record · LEDGER

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation

As of 17 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2506.01116.

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

pith.paper-citation-record.v1
2506.01116 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:56:45.062385Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

32 of 32 outbound references displayed

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Outbound references

Observation 74775eeb-461b-413d-9b39-576b6ec4d394 · outbound

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

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2

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Observation d50e921c-ebbc-4cdb-9c12-8de10c1f4d9e · outbound

This paper cites Can Large Language Models Empower Molecular Property Prediction?.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Can Large Language Models Empower Molecular Property Prediction?

Reference 5

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Observation d051a7e7-0e0f-4ec2-a1ff-870030939677 · outbound

This paper cites CRISPR-GPT for Agentic Automation of Gene-editing Experiments.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation CRISPR-GPT for Agentic Automation of Gene-editing Experiments

Reference 6

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Observation e4011fd3-db26-43c5-963e-9a8b49d3119f · outbound

This paper cites Molgpt: molecular generation using a transformer- decoder model.Journal of chemical information and modeling, 62(9):2064–2076,.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Molgpt: molecular generation using a transformer- decoder model.Journal of chemical information and modeling, 62(9):2064–2076,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation a92c7d9f-e7e6-4034-ba52-9f2bfb6a0851 · outbound

This paper cites Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey

Reference 10

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Observation c4ad12f7-8bf7-4960-95b9-1f84ea729238 · outbound

This paper cites Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models

Reference 11

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Observation 47077c10-440d-4a45-8584-c3011a801481 · outbound

This paper cites An Evaluation of Estimative Uncertainty in Large Language Models.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation An Evaluation of Estimative Uncertainty in Large Language Models

Reference 12

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Observation 97b68809-8e63-4ee9-a807-ac261647c27f · outbound

This paper cites Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 13

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Observation 45b78b8e-3e05-4d6d-ab5f-88c72ed0c96f · outbound

This paper cites Qwen2.5 Technical Report.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Qwen2.5 Technical Report

Reference 14

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Observation ede036bb-d3af-410b-b5ee-06d651c0b634 · outbound

This paper cites The Llama 3 Herd of Models.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation The Llama 3 Herd of Models

Reference 15

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Observation dfecdaff-ea71-4f08-b759-535392778f87 · outbound

This paper cites SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

Reference 16

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Observation f037a8fc-1ef2-457b-9f6b-07ae18cc217c · outbound

This paper cites Uncertainty quantification in fine-tuned LLMs using LoRA ensembles.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

Reference 17

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Observation b243e6ef-ed52-45c7-a122-9f6e8afe3b93 · outbound

This paper cites A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 18

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Observation 40f61e05-de6c-47cc-978a-c48e3fb407e2 · outbound

This paper cites The Internal State of an LLM Knows When It's Lying.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation The Internal State of an LLM Knows When It's Lying

Reference 19

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Observation 3c4030f0-5d0e-4b20-9e67-9a5c69f6eeac · outbound

This paper cites LUQ: Long-text Uncertainty Quantification for LLMs.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation LUQ: Long-text Uncertainty Quantification for LLMs

Reference 20

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Observation 98d426e1-c16a-419b-a889-00bb86e72a03 · outbound

This paper cites SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Reference 21

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Observation b38c3eba-8063-457a-8b6e-d0e271d4e1a8 · outbound

This paper cites Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification

Reference 22

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Observation 20380fef-f2ab-4b59-98cc-47e18c263dc1 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 23

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Observation 16344db3-8d34-42bc-beee-9f8421f93fe1 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 24

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Observation 29ea4101-d7a4-4e99-8363-b0e2dcfac7ae · outbound

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ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation BERTScore: Evaluating Text Generation with BERT

Reference 25

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Observation 4853dc53-6b14-4810-be50-d4e00f63bd33 · outbound

This paper cites Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 26

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Observation 7614c7e4-f6d9-46ca-ae2e-60d53e3e54fe · outbound

This paper cites AmbigQA: Answering Ambiguous Open-domain Questions.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation AmbigQA: Answering Ambiguous Open-domain Questions

Reference 27

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Observation 9d23566b-9421-477a-a6db-d80620c3892b · outbound

This paper cites Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

Reference 29

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Observation d0288b76-e618-4ed2-bbf7-461592e4bd5d · outbound

This paper cites Developing ChemDFM as a large language foundation model for chemistry.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Developing ChemDFM as a large language foundation model for chemistry

Reference 30

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Observation 2301abcb-0dfb-4bc8-96d2-e9fd3d7a7d6a · outbound

This paper cites ChemEval: A Comprehensive Multi-Level Chemical Evaluation for Large Language Models.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation ChemEval: A Comprehensive Multi-Level Chemical Evaluation for Large Language Models

Reference 31

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ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models

Reference 32

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Observation bc4d98f9-5285-498d-8c6f-4867475aa036 · outbound

This paper cites SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery

Reference 2019

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Observation 3cda15e2-9b5d-4b2c-b36d-98f0df90a1a4 · outbound

This paper cites CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models

Reference 2020

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Observation 3b95943a-dea8-4a8b-b7ef-60a286f5f940 · outbound

This paper cites Self-Reflection in LLM Agents: Effects on Problem-Solving Performance.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Self-Reflection in LLM Agents: Effects on Problem-Solving Performance

Reference 2022

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Observation 3af94bf8-c2d9-46c8-a5ee-b178c2b41935 · outbound

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ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation GPT-4 Technical Report

Reference 2023

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Observation 2df0fa21-1272-4e55-a493-b1785495c368 · outbound

This paper cites LegalAgentBench: Evaluating LLM Agents in Legal Domain.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 2024

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This paper cites ChemLLM: A Chemical Large Language Model.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation ChemLLM: A Chemical Large Language Model

Reference 2025

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Pith citing papers

No inbound Pith citation observations are available.