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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 2026-08-21T06:32:19.484+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 2026-08-21T06:32:19.484+00:00.

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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.

source=pdf_text observed=2026-08-10T00:39:02.667986Z digest=sha256:0c6399fce653ff4178a1db7532a1852d3de7807885b840a77dd0f67f7983b541

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.671907Z digest=sha256:fe9cf81460c1ab5e475a828c02a971f17122fc2d39e476c6554d96e285ef85ac

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.675219Z digest=sha256:5b2b8c6a877fb5a5dbbaa1db96df91cf88921079ed69b6b05f3c24e25ac74504

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.678843Z digest=sha256:d7f400ca178fc051a516288d93d481b423c121301f3898e7b83b950939645c91

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.682391Z digest=sha256:a24d84098066a321b646f6e59899f145fe5677fa76adb36186c648f8c7a4d171

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.686265Z digest=sha256:977cde6db8155f269c0578e82fd23ae1eb32dca4f4b20d1fa956f563cd8abc20

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.689847Z digest=sha256:ba3796c0428c231557964ec5cc6c316d5e76bf66fa4b4123f89003d0172ca6ac

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.693571Z digest=sha256:e48daa72b6b5b922273ada7270dd5dbef5603231e1ff4f0e066be01b94697ecb

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.697238Z digest=sha256:972c564c49c08e09380f9b31196e635c33673e20549d064187cbaa7e64ad1411

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.700859Z digest=sha256:da138f8d16d28e11856a50120c33ac6465eb9b1bd46ebcdf811a4c229c84cef0

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.704396Z digest=sha256:14454579d56823d4efb97a57728494c00190c45b9ad61e5045c2dc0d7958d06c

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.708024Z digest=sha256:ad413a98e50ff707b799383431113b0eb8fcfa7337a62953a3b0352bbee77298

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.711881Z digest=sha256:3d04025bbb1b6d3ed2836a9477565ac16dd8dea0ed158a67dd08b4fa054d7a02

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.716204Z digest=sha256:55e8b06e463578de8b2786d42713daa9beee17825de06e97561894fcce57dccd

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.719787Z digest=sha256:c948c3473063c5a51314a6c3cbe97eaf3ba611c9dff776852bbf107eb74875c8

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.723302Z digest=sha256:292f7d5ad609891427371039103c815f81fb04393af156914a46e0f0e10a97aa

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.727249Z digest=sha256:82bbb23b7c2fab4fca70b3264f8ace53388f64feea84c99de14faee33c25cb53

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.730849Z digest=sha256:69cebf83da8c4039daefdce4a6412e81c8d92d9194278c0f07dc8bc68e39bd1d

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.733952Z digest=sha256:d605739bde2c486ce5cc7b0b0280c236d5a1de2c2b22a9f582633dfac86e9ea8

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.737422Z digest=sha256:db20c4f166add77594c84a72b234c6b329a4ce8faf91af8ecce8c13792541365

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.740457Z digest=sha256:a683577b0f22759a4b9ca8413dfb6ff4177a39a5070fbdc38171cb846c4c34f3

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.743750Z digest=sha256:0f2c4c05d365ab55e9d61c027bc5ba01f66a916f48d1856c665312d9e63c5504

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:39:02.746982Z digest=sha256:0566b38974050092c4ccdea75782d5aeedf3b5addbd424d3cd6e51508d8175e4

Pith citing papers

No inbound Pith citation observations are available.