Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:37:59.867130Z
Paper Citation Record · LEDGER
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions
As of 22 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2507.07745.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
19 of 19 outbound references displayed
- verified exact0
- verified fuzzy12
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bcc87701-17f9-4376-bb67-dba94bfb1467 · outbound
This paper cites Artificial intelligence: A powerful paradigm for scientific research,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Artificial intelligence: A powerful paradigm for scientific research,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.381600Z
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.
Observation a37744c2-f21b-4bff-b397-dd4f61cc2bd2 · outbound
This paper cites A compact guide to learn large language models,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions A compact guide to learn large language models,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.355362Z
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.
Observation 76c417ff-6d85-4813-9939-f47360d132ec · outbound
This paper cites Wulff, M.
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.328143Z
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.
Observation fbc8a4bb-0d38-49ee-a0b8-92b29ba82fec · outbound
This paper cites Bisong, Building Machine Learning and Deep Learning Models on Google Cloud Platform: A Comprehensive Guide for Beginners , 01 2019.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Bisong, Building Machine Learning and Deep Learning Models on Google Cloud Platform: A Comprehensive Guide for Beginners , 01 2019
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.304276Z
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.
Observation cc568658-2581-4350-a0dd-5df3ffe29ac5 · outbound
This paper cites Attention is all you need,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Attention is all you need,
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:37:59.766950Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 99387fa5-24da-4fa9-9f0c-0ad38b1c3686 · outbound
This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Bert: Pre-training of deep bidirectional transformers for language understanding,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.253534Z
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.
Observation 40d5835a-9fdc-422c-b447-d67ab1998fda · outbound
This paper cites Improving language understanding by generative pre-training,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Improving language understanding by generative pre-training,
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:37:59.791038Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43af6390-341a-4e07-8490-5d132dec0d47 · outbound
This paper cites Recent progress in semantic image segmentation,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Recent progress in semantic image segmentation,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.211216Z
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.
Observation 6d28094d-0469-4c48-8d89-459bb5164220 · outbound
This paper cites A dnn-based semantic segmentation for detecting weed and crop,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions A dnn-based semantic segmentation for detecting weed and crop,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.190231Z
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.
Observation f42fe2de-1d6b-4532-b910-be23cd89f612 · outbound
This paper cites Unifying motion segmentation, estimation, and tracking for complex dynamic scenes,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Unifying motion segmentation, estimation, and tracking for complex dynamic scenes,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.164322Z
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.
Observation 6bd17bdc-c430-4fa7-bf99-a90b47889099 · outbound
This paper cites An organizing principle for a class of voluntary move- ments,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions An organizing principle for a class of voluntary move- ments,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.136602Z
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.
Observation 27e40be6-ab9c-4945-a767-779fada8e75b · outbound
This paper cites Temporal convolutional networks for action segmentation and detection,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Temporal convolutional networks for action segmentation and detection,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.116057Z
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.
Observation 5c08c428-1dc7-44d4-9d02-fd1f34e7ccfd · outbound
This paper cites Temporal convolutional networks: A unified approach to action segmentation,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Temporal convolutional networks: A unified approach to action segmentation,
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:37:59.830022Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d29f537f-109e-4fc3-907d-d5aafb0b7783 · outbound
This paper cites On estimating regression,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions On estimating regression,
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:37:59.838554Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d30b5c46-8dd4-4247-8a22-10580d09181d · outbound
This paper cites Smooth regression analysis,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Smooth regression analysis,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:38:00.062018Z
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.
Observation 61fd070c-bc7a-4440-b659-f28345fecfb9 · outbound
This paper cites an unresolved cited work.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:38:00.039786Z
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.
Observation 6d12c2b3-5d7b-498c-b865-eb1191548613 · outbound
This paper cites an unresolved cited work.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:37:59.998533Z
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.
Observation ab16b7a8-e587-4baf-89f5-372a177c375f · outbound
This paper cites Exponential stability of an attitude trajectory tracking controller utilizing unit quaternions,.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Exponential stability of an attitude trajectory tracking controller utilizing unit quaternions,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:37:59.970987Z
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.
Observation 9dc6db1a-1b54-462e-8944-6e9c42064a21 · outbound
This paper cites Attention Is All You Need.
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Attention Is All You Need
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:37:59.774590Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.