Paper Citation Record · LEDGER

Battery State of Health Estimation Using LLM Framework

As of 21 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2501.18123.

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

pith.paper-citation-record.v1
2501.18123 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T00:39:02.746982Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

verified exact4
verified fuzzy18
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e7481e20-0aba-452a-bd63-42ec5bd7a3a0 · outbound

This paper cites Lithium titanate oxide battery cells for high-power automotive applications – electro- thermal properties, aging behavior and cost considerations,.

Battery State of Health Estimation Using LLM Framework Lithium titanate oxide battery cells for high-power automotive applications – electro- thermal properties, aging behavior and cost considerations,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:03.061644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7069e37a-58b5-482e-bcb0-2ae6cadd4355 · outbound

This paper cites Multimodal LLM for Intelligent Transportation Systems.

Battery State of Health Estimation Using LLM Framework Multimodal LLM for Intelligent Transportation Systems

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T00:39:02.667986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 259a4e8a-e0db-4ebe-8779-7a6a8668f943 · outbound

This paper cites Lithium titanate battery system enables hybrid electric heavy-duty vehicles,.

Battery State of Health Estimation Using LLM Framework Lithium titanate battery system enables hybrid electric heavy-duty vehicles,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:03.050582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c9f00b97-d99c-4ac6-95c0-9fa65e0eba58 · outbound

This paper cites Advancing state of health estimation for electric vehicles: Transformer-based approach leveraging real-world data,.

Battery State of Health Estimation Using LLM Framework Advancing state of health estimation for electric vehicles: Transformer-based approach leveraging real-world data,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:03.039755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b319cb00-b2dc-481e-af4a-494ab2753ae0 · outbound

This paper cites Battery management,.

Battery State of Health Estimation Using LLM Framework Battery management,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:03.028176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 457d99a2-488f-4593-9ffa-baff5e58e2e4 · outbound

This paper cites Accelerating Sensor Fusion in Neuromorphic Computing: A Case Study on Loihi-2.

Battery State of Health Estimation Using LLM Framework Accelerating Sensor Fusion in Neuromorphic Computing: A Case Study on Loihi-2

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-10T00:39:02.841618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1016403e-76f9-4385-b82e-69d76c70d82c · outbound

This paper cites A Survey of Spiking Neural Network Accelerator on FPGA.

Battery State of Health Estimation Using LLM Framework A Survey of Spiking Neural Network Accelerator on FPGA

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-10T00:39:02.825080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8f88e364-4e9d-4737-8ec7-9665329bf299 · outbound

This paper cites A review of soh estimation methods in lithium-ion batteries for electric vehicle applications,.

Battery State of Health Estimation Using LLM Framework A review of soh estimation methods in lithium-ion batteries for electric vehicle applications,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:03.015346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 009c16c1-014e-46f2-850b-f03e5eaa4f2c · outbound

This paper cites A review of battery state of health estimation methods: Hybrid electric vehicle challenges,.

Battery State of Health Estimation Using LLM Framework A review of battery state of health estimation methods: Hybrid electric vehicle challenges,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:03.003847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 67e51765-57b5-4e9d-af8d-e4bbe7e530e8 · outbound

This paper cites A machine learning approach for evaluation of battery state of health,.

Battery State of Health Estimation Using LLM Framework A machine learning approach for evaluation of battery state of health,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.992823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 525c44e3-724b-4c00-91e2-89eed82f78fe · outbound

This paper cites State of health estimation and prediction of electric vehicle power battery based on operational vehicle data,.

Battery State of Health Estimation Using LLM Framework State of health estimation and prediction of electric vehicle power battery based on operational vehicle data,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.982021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f6bd536b-a7a7-420c-aa0b-0ad6590e9c60 · outbound

This paper cites Lithium- ion battery state of health estimation using support vector regression (svr),.

Battery State of Health Estimation Using LLM Framework Lithium- ion battery state of health estimation using support vector regression (svr),

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.969720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ce2b4a2d-9ec3-4e36-82ef-79a401992ab4 · outbound

This paper cites Adaptive large language model for predicting lithium-ion battery degradation in energy storage systems,.

Battery State of Health Estimation Using LLM Framework Adaptive large language model for predicting lithium-ion battery degradation in energy storage systems,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.959278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e9a42454-01ee-4dbd-8d6a-7fdab4ffbc31 · outbound

This paper cites SHIELD: LLM-Driven Schema Induction for Predictive Analytics in EV Battery Supply Chain Disruptions.

Battery State of Health Estimation Using LLM Framework SHIELD: LLM-Driven Schema Induction for Predictive Analytics in EV Battery Supply Chain Disruptions

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-10T00:39:02.809188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 20d5a9c4-8c51-4c6f-a72f-604e0e898b55 · outbound

This paper cites Hybrid prompt-driven large language model for robust state-of-charge estimation of multi-type li-ion batteries,.

Battery State of Health Estimation Using LLM Framework Hybrid prompt-driven large language model for robust state-of-charge estimation of multi-type li-ion batteries,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.949485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 893b878a-de27-4b36-80f2-443a0453c2d1 · outbound

This paper cites State of health estimation of lithium titanate oxide batteries through data-driven techniques and machine learning,.

Battery State of Health Estimation Using LLM Framework State of health estimation of lithium titanate oxide batteries through data-driven techniques and machine learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.939198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a805638b-027d-469c-bcb7-b1780d94956c · outbound

This paper cites Sundén, Hydrogen, Batteries and Fuel Cells.

Battery State of Health Estimation Using LLM Framework Sundén, Hydrogen, Batteries and Fuel Cells

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.928594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 90d8b3dd-446f-4188-9973-fd37294be000 · outbound

This paper cites Adapting Amidst Degradation: Cross Domain Li-ion Battery Health Estimation via Physics-Guided Test-Time Training.

Battery State of Health Estimation Using LLM Framework Adapting Amidst Degradation: Cross Domain Li-ion Battery Health Estimation via Physics-Guided Test-Time Training

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T00:39:02.793720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d9089ab7-867c-4c33-8c26-1fbf339e4e17 · outbound

This paper cites Transformer-based deep learning models for state of charge and state of health estimation of li-ion batteries: A survey study,.

Battery State of Health Estimation Using LLM Framework Transformer-based deep learning models for state of charge and state of health estimation of li-ion batteries: A survey study,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.917150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ff57fd73-9c13-49f5-83a6-2ae914a4340a · outbound

This paper cites Deep learning approach towards accurate state of charge estimation for lithium-ion batteries using self-supervised transformer model,.

Battery State of Health Estimation Using LLM Framework Deep learning approach towards accurate state of charge estimation for lithium-ion batteries using self-supervised transformer model,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.905689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation acddc7c8-11f1-4e66-986c-65203c245e5b · outbound

This paper cites Review of battery state estimation methods for electric vehicles-part ii: Soh estimation,.

Battery State of Health Estimation Using LLM Framework Review of battery state estimation methods for electric vehicles-part ii: Soh estimation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.893263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 25ad9c28-e101-4395-a770-f4a86a69bb3f · outbound

This paper cites Data-driven methods for battery soh estimation: Survey and a critical analysis,.

Battery State of Health Estimation Using LLM Framework Data-driven methods for battery soh estimation: Survey and a critical analysis,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.880434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 649bd1d2-a15b-4cc3-a114-f6bf7e595288 · outbound

This paper cites State of health and remaining useful life prediction of lithium-ion batteries based on a disturbance-free incremental capacity and differential voltage analysis method,.

Battery State of Health Estimation Using LLM Framework State of health and remaining useful life prediction of lithium-ion batteries based on a disturbance-free incremental capacity and differential voltage analysis method,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:39:02.867745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d1cee965-a2fa-43e8-a7c0-fe461251a878 · outbound

This paper cites Lto battery capacity fading,.

Battery State of Health Estimation Using LLM Framework Lto battery capacity fading,

Reference 24

Resolution: verified exact; doi, observed 2026-08-10T00:39:02.777139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.