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Paper Citation Record · LEDGER

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

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 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 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:39:41.417796Z

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 badd4261-d3f7-4ec1-a31e-acf65d2accf5 · inbound

mmEgoHand: Egocentric Hand Pose Estimation and Gesture Recognition with Head-mounted Millimeter-wave Radar and IMU cites this paper.

mmEgoHand: Egocentric Hand Pose Estimation and Gesture Recognition with Head-mounted Millimeter-wave Radar and IMU SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognition

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T15:39:41.417796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:39:41.417796Z digest=sha256:2c35a6b2d731f7192a1509fb1ba9fee6670a2db70663bae4f6787df7269aa4d2

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-23T01:03:30.923298Z digest=sha256:f3110adca0a1f8bc31196b4ba06fe4090ec9c52ec759ca6a85254aa05a6abf71

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.

source=pdf_text observed=2026-08-07T14:30:36.757560Z digest=sha256:00865f21b3aff95ba6be29a46650fcc8aad3b7c8776471e2967f76fc3099aca5

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-19T09:31:55.829045Z digest=sha256:99b664d8dbe1abddf838cd671631e1f41dcb22fe9fbe30baa733d9f6ed56305e

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-21T06:09:44.172188Z digest=sha256:41f11ad71a05d73f829d9c9625fe723c160873b732e3e1bb566aa98f2662c53d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-27T13:55:15.627610Z digest=sha256:62898efd23d8a1d26ca5deb38f79cb2f12d317de15211057a6ec74c5cd0cba7f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-26T09:34:00.058213Z digest=sha256:de788123ea6dd2a1f670fdc4a6d58f1a9d601ed4094e56996e30187f4decd367