Paper Citation Record · LEDGER

SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognition

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.10624.

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

pith.paper-citation-record.v1
2410.10624 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:30:36.757560Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0777850e-2f78-4ae3-8520-4a82eaf82591 · inbound

COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity Recognition cites this paper.

COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity Recognition SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognition

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:05:16.124255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1b95267f-a190-4a6b-a9da-cf81f6b44549 · inbound

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection cites this paper.

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognition

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:30:36.757560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0910de5-4ad5-4bd2-ab05-63f13590b58e · inbound

From Time Series Analysis to Question Answering: A Survey in the LLM Era cites this paper.

From Time Series Analysis to Question Answering: A Survey in the LLM Era SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognition

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:32:15.899067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c15ab9ca-c1f9-4f79-a5bb-cbc68ffd3d7c · inbound

TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health cites this paper.

TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognition

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:13:59.473535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bd3ec208-97b1-4c44-bcaa-1df7db28dc28 · inbound

Closing the Modality Gap in Zero-Shot HAR: Contrastive Training and Separability-Optimized Prototypes on IMU Data cites this paper.

Closing the Modality Gap in Zero-Shot HAR: Contrastive Training and Separability-Optimized Prototypes on IMU Data SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognition

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:27:36.794757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f58efc4c-b130-4375-bbd4-9035b1b58a62 · inbound

Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing cites this paper.

Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognition

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:49:44.096009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.