Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:37:59.867130Z
Paper Citation Record · LEDGER
As of 19 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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:37:59.867130Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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
19 of 19 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation bcc87701-17f9-4376-bb67-dba94bfb1467 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a37744c2-f21b-4bff-b397-dd4f61cc2bd2 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 76c417ff-6d85-4813-9939-f47360d132ec · outbound
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fbc8a4bb-0d38-49ee-a0b8-92b29ba82fec · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cc568658-2581-4350-a0dd-5df3ffe29ac5 · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 99387fa5-24da-4fa9-9f0c-0ad38b1c3686 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 40d5835a-9fdc-422c-b447-d67ab1998fda · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43af6390-341a-4e07-8490-5d132dec0d47 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6d28094d-0469-4c48-8d89-459bb5164220 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f42fe2de-1d6b-4532-b910-be23cd89f612 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6bd17bdc-c430-4fa7-bf99-a90b47889099 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 27e40be6-ab9c-4945-a767-779fada8e75b · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5c08c428-1dc7-44d4-9d02-fd1f34e7ccfd · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d29f537f-109e-4fc3-907d-d5aafb0b7783 · outbound
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions On estimating regression,
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d30b5c46-8dd4-4247-8a22-10580d09181d · outbound
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Smooth regression analysis,
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 61fd070c-bc7a-4440-b659-f28345fecfb9 · outbound
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Unresolved cited work
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6d12c2b3-5d7b-498c-b865-eb1191548613 · outbound
On the capabilities of LLMs for classifying and segmenting time series of fruit picking motions into primitive actions Unresolved cited work
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ab16b7a8-e587-4baf-89f5-372a177c375f · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9dc6db1a-1b54-462e-8944-6e9c42064a21 · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.