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Paper Citation Record · LEDGER

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs

As of 7 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 2 inbound Pith citation observations for arXiv:2507.13737.

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

pith.paper-citation-record.v1
2507.13737 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:22:33.080354Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T06:09:44.172188Z

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

44 of 44 outbound references displayed

  • verified exact1
  • verified fuzzy31
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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

Outbound references

Observation 9d85eec3-1a3f-4168-ab7b-70f2e6045e46 · outbound

This paper cites (2025) Global smartphone penetration 2016-.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs (2025) Global smartphone penetration 2016-

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:39.275040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.873487Z digest=sha256:c3a7a4530b2b76ecdbb24eb2ef59a0be6d464a8555a9b12674ed636a8a881a4d

Observation 48f730e5-fe31-499a-9e60-33d679618f03 · outbound

This paper cites Life-tags: a smartglasses-based system for recording and abstracting life with tag clouds,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Life-tags: a smartglasses-based system for recording and abstracting life with tag clouds,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:38.933216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.884243Z digest=sha256:22591331c6654a6f53bca805d2711ca812be81848b9ba89d6ad350409cf6f975

Observation 6c57b621-71e8-4d83-94ce-89f3969001a7 · outbound

This paper cites Memento: An emotion-driven lifel- ogging system with wearables,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Memento: An emotion-driven lifel- ogging system with wearables,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:38.700408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.889321Z digest=sha256:fd55d7dd3c789e0fff47ce0f742f1b1acaef41fbf3878587e876d0c44a2f1de0

Observation 9afe49a5-f8f8-46b8-a3f5-ab2e7b2e7873 · outbound

This paper cites Integrating extended reality and neural headsets for enhanced emotional lifelogging: A technical overview,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Integrating extended reality and neural headsets for enhanced emotional lifelogging: A technical overview,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:38.417637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.894134Z digest=sha256:217691d2f6000ad9df6cbbb2d9fb972c4d5d01d9e82dc019d75bbaa4c07682d5

Observation 3b772d1a-04dc-48ad-aab6-57cacbf64a0c · outbound

This paper cites AutoLife: Automatic Life Journaling with Smartphones and LLMs.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs AutoLife: Automatic Life Journaling with Smartphones and LLMs

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:32.899061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:32.899061Z digest=sha256:4bea650f771e78276159259be28af1e456d654982014c79a9e137c1fff7c3e83

Observation c220563d-e975-4c33-ba7f-91a038a90819 · outbound

This paper cites Contextllm: Meaningful context reasoning from multi-sensor and multi- device data using llms,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Contextllm: Meaningful context reasoning from multi-sensor and multi- device data using llms,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:38.066931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.904812Z digest=sha256:065b518cd4f3dda696148e52c9126213187770ca2077a23b9b3c93fc7e69fce2

Observation 08d942f1-a12a-4e11-b4d8-9d6103443f05 · outbound

This paper cites Lifelog: Timelog & diary,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Lifelog: Timelog & diary,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:37.790162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.909372Z digest=sha256:01c47c118961a4ca32d3e4fb6c31b45401cc9d1d5b63ed73876e47f016ec797b

Observation 51d53ba6-f6f3-4c4e-9c7c-a7538bd54b67 · outbound

This paper cites (2025) Day one journal app — your journal for life.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs (2025) Day one journal app — your journal for life

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:37.561133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.913880Z digest=sha256:2d145c51afecbf0b6f7ed37bc1498f44fcd674e8408b36a9ae84d7fd7c49697d

Observation c04e9839-e46b-4ec9-820b-c3fa69d48813 · outbound

This paper cites Foodai: Food image recognition via deep learning for smart food logging,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Foodai: Food image recognition via deep learning for smart food logging,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:37.328374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.918745Z digest=sha256:a75afb4568efa512015e249ffe7b8cf187297bc5b48b111d2b56558c2fdf3659

Observation 0cd3106b-03fe-4a36-ab68-3caf758018ce · outbound

This paper cites Cyberslacking or smart work: Smart- phone usage log-analysis focused on app-switching behavior in work and leisure conditions,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Cyberslacking or smart work: Smart- phone usage log-analysis focused on app-switching behavior in work and leisure conditions,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:37.163239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.923186Z digest=sha256:faf06afc1a3fb6b5aa47645719dd882ae53c683512b220e5a35840bb18de47a2

Observation a4698fa8-e5d6-41e7-87cf-d2406c36520e · outbound

This paper cites Analyzing mobile application usage: generat- ing log files from mobile screen recordings,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Analyzing mobile application usage: generat- ing log files from mobile screen recordings,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:37.000115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.928086Z digest=sha256:e03a612b8171453a0f902fe56152a7b4c628d5cbfd8357593f33e0447f1750ff

Observation 934a011b-9520-4a50-9036-948438e16753 · outbound

This paper cites A novel voice interactive sleep log: concurrent validity with actigraphy and sleep diaries,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs A novel voice interactive sleep log: concurrent validity with actigraphy and sleep diaries,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:36.775276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.933097Z digest=sha256:e2408caf98ee422408782933c657dae40940cae38384d9ca76bf506ea87d2ae6

Observation a0a7c044-2b64-4d40-a312-69b8a093c24a · outbound

This paper cites Lora: Low-rank adaptation of large language models.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Lora: Low-rank adaptation of large language models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:32.937930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:32.937930Z digest=sha256:8e6b5a2d2e160bf840ba1dc9b3b3aea2147c71da6a502e2ac9bc03a1a0d5453a

Observation ec42a46f-f67b-44a0-846b-0d8448ab2ac0 · outbound

This paper cites Llasa: Large multimodal agent for human activity analysis through wearable sensors,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Llasa: Large multimodal agent for human activity analysis through wearable sensors,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:32.942882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:32.942882Z digest=sha256:8143fae6434e70579c509d33277bef2b56ba021b0f16899635aa2513d4e40761

Observation 7aebe72f-4e22-4ea2-a09e-76741b21e607 · outbound

This paper cites When iot meet llms: Applications and challenges,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs When iot meet llms: Applications and challenges,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:36.637182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.947380Z digest=sha256:923b1fa0fc1d481cf53592897291d8225af43899587bcfba9288211f01fadc75

Observation c37a6c74-4b38-42c7-9e07-ed0746516867 · outbound

This paper cites Iot-llm: Enhancing real- world iot task reasoning with large language models,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Iot-llm: Enhancing real- world iot task reasoning with large language models,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:32.951979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:32.951979Z digest=sha256:cbd64087d0016127b747ebad07c1c40509898a3afd9312001a396d04ef0e533c

Observation 4580cc77-1e9b-4be0-accc-81986744eac6 · outbound

This paper cites IoT-LM: Large Multisensory Language Models for the Internet of Things.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs IoT-LM: Large Multisensory Language Models for the Internet of Things

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:32.956321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:32.956321Z digest=sha256:19996b3d3be4672669869f86f16f562e00237f08d3324fdf82450438b952cbfb

Observation 2460415f-be07-4ff4-9955-bef84851a076 · outbound

This paper cites Penetrative ai: Making llms comprehend the physical world,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Penetrative ai: Making llms comprehend the physical world,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:32.960865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:32.960865Z digest=sha256:2307c65ec2f099b68864f1d0a9fc5563e0d97f6875a5e83bf5d1efaf5deb8f4a

Observation 141c2fe3-64b9-4fb4-8f05-11f60197c9c5 · outbound

This paper cites HARGPT: Are LLMs Zero-Shot Human Activity Recognizers?.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs HARGPT: Are LLMs Zero-Shot Human Activity Recognizers?

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:32.964742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:32.964742Z digest=sha256:596f662a67303bf74e554ebdb834862ef6528f158cd5f546fcd302e20784442c

Observation 92b98f28-956c-48d4-98a9-d9a3dfdbfb60 · outbound

This paper cites Evaluating large language models as virtual annotators for time-series physical sensing data,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Evaluating large language models as virtual annotators for time-series physical sensing data,

Reference 20

Resolution
verified exact
doi, observed 2026-08-06T16:22:33.119685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.969360Z digest=sha256:2f3420ba5138b4ec7ecf839e4fbe6e8624aee99ae25851505387f6c9e742ac88

Observation 9462c8e7-69d9-4c8c-ad8a-a4205e44ea18 · outbound

This paper cites Using large language models to enhance the reusability of sensor data,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Using large language models to enhance the reusability of sensor data,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:36.426032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.973759Z digest=sha256:15e4700b9db6d576b0d01cea65c207d381490ac3d483079fa15f7fcc0b2f61e9

Observation 8554e9cc-fbd6-4e0d-bf9f-111031bc778a · outbound

This paper cites Barometric formula — wikipedia, the free encyclopedia,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Barometric formula — wikipedia, the free encyclopedia,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:36.227973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.978103Z digest=sha256:6bf74ac8e94e3fa918f08d2c7658b0cd34822fe194a3cd9fe15d60049fbfb051

Observation 380c5eda-ac28-432b-a228-0f16b98e7bed · outbound

This paper cites Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:32.982306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:32.982306Z digest=sha256:7edefff1918645747bc38319436074614e3a67e99e094c39114d01e17d4ca564

Observation 3f7c81ec-111d-4cf7-8c32-630379899e7f · outbound

This paper cites DeepSeek-V3 Technical Report.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs DeepSeek-V3 Technical Report

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:32.986599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:32.986599Z digest=sha256:c107ebd6ce5e7a33eabf3e9e004e6a3545c601c48d1c3500b2cf72383cf840ad

Observation 36fdc760-3a56-4a46-ace0-a279fb07d0bc · outbound

This paper cites Studentlife: assessing mental health, academic performance and behavioral trends of college students using smartphones,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Studentlife: assessing mental health, academic performance and behavioral trends of college students using smartphones,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:36.058835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.991024Z digest=sha256:ca626b5b8a3f580581f4acb15d1895e55f372dec268d2e81150467bcbaf58bf9

Observation ac589c6d-573b-48c1-a51d-1380c00b2232 · outbound

This paper cites Smart devices are different: Assessing and mitigatingmobile sensing heterogeneities for activity recognition,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Smart devices are different: Assessing and mitigatingmobile sensing heterogeneities for activity recognition,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:35.888872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.995285Z digest=sha256:cc4603ac73dd7653c1dcac07e7d03277a3c098a794545468524019e76c79fd99

Observation 98a716ff-1aab-4877-a177-58d72c0f5e03 · outbound

This paper cites Mobile sensor data anonymization,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Mobile sensor data anonymization,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:35.704514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.999793Z digest=sha256:8539f207fd60a013a0ac7f4f2c92273b7a6192b229def301b6a9fe60eeb738b9

Observation 6574acd5-984c-4d5e-9d2a-f71a9312475a · outbound

This paper cites Fusion of smartphone motion sensors for physical activity recognition,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Fusion of smartphone motion sensors for physical activity recognition,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:35.503109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.004100Z digest=sha256:6726547c5d4f7b36e32ecee60fad40c6301a5ed5a0d4a4f549101423211afeb5

Observation 2e7e654c-f860-418d-bd32-89504c7d7786 · outbound

This paper cites Transition-aware human activity recognition using smartphones,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Transition-aware human activity recognition using smartphones,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:35.265198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.008827Z digest=sha256:8864ffaae149ebef08cf7022ceb6ea83bdceab68a151e7529fddade41cb9ee95

Observation fb4681f6-9adf-4962-b516-fcf553f82614 · outbound

This paper cites Mesaros, T.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Mesaros, T

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:35.078206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.014122Z digest=sha256:1dd9201aacbaed356da29b7a0b1fd6aa61a808a297c81e6c5e67aade5ee451d8

Observation 3dcf1588-9582-492c-80d5-8fe6f704b81f · outbound

This paper cites DCASE 2017 challenge setup: Tasks, datasets and baseline system,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs DCASE 2017 challenge setup: Tasks, datasets and baseline system,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:34.882186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.018809Z digest=sha256:fe14c1e4f4f3e9a368b87c5aaefe33b746f7dcfeaa604fd932c11c7703795cf5

Observation 7f2d8f0d-2466-4bbd-8226-7c5905f56acd · outbound

This paper cites Introducing wesad, a multimodal dataset for wearable stress and affect detection,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Introducing wesad, a multimodal dataset for wearable stress and affect detection,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:34.690139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.024035Z digest=sha256:08232126f335b68e2bfc5df763538e5941b0fe02deb41593976ea2fa3edb7154

Observation 3aeeacc7-616c-4c9f-a1db-0222232f7355 · outbound

This paper cites Human activities recognition in android smartphone using support vector machine,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Human activities recognition in android smartphone using support vector machine,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:34.493713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.030044Z digest=sha256:d433fdb644569dc467f6fc98ca58be2d6e84a6d5869385bb3f85583833825516

Observation e05c4ec1-d46d-4042-a329-9c1a82eae95d · outbound

This paper cites Human activity recognition using k-nearest neighbor machine learning algorithm,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Human activity recognition using k-nearest neighbor machine learning algorithm,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:34.294027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.035348Z digest=sha256:1f4c51209ce9972f99352c5f3caac794f36319b8af96f30f1ce9b216f04f30d5

Observation 7c976cee-a5e1-4fe6-98ac-9887de909d23 · outbound

This paper cites Cnn-based sensor fusion techniques for multimodal hu- man activity recognition,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Cnn-based sensor fusion techniques for multimodal hu- man activity recognition,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:34.101947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.040012Z digest=sha256:1d53ce2878cc88025ce2dd259bc112983fba1791840a814719b8c74d6c579c45

Observation 50b786c2-8917-4ee4-a3da-6bfcd76162d7 · outbound

This paper cites Lstm networks for mobile human activity recognition,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Lstm networks for mobile human activity recognition,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:33.918591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.044880Z digest=sha256:4ede8e5a3f2b55c8edaa4919a289a1f432015d5e03d79ac4ded32d79cac4b373

Observation 30f7d3ed-246d-4c25-8f74-7a4d31f500fd · outbound

This paper cites Supervised nonnegative matrix factorization for acoustic scene classification,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Supervised nonnegative matrix factorization for acoustic scene classification,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:33.687843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.049885Z digest=sha256:c397cfe538cb293d15e69ded84e55dc018c153d0081cea9c39a7490118f40ea3

Observation a86e9b21-5411-435c-be06-08f26757f85f · outbound

This paper cites Convolutional neural networks with binaural repre- sentations and background subtraction for acoustic scene classification,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Convolutional neural networks with binaural repre- sentations and background subtraction for acoustic scene classification,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:33.534963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.055299Z digest=sha256:7bd489e8afe951c3ca67beee23b68410a786ef0bebd2c46513b2e8dab3792638

Observation a0f895c2-c9eb-4649-b63f-002cd23daeb6 · outbound

This paper cites Raspberry pi 5,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Raspberry pi 5,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:33.488048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.060314Z digest=sha256:73f40b5f2c0cabc58e46bf7d44ab015b77a2bd332feedd58df2b947d75d580b9

Observation f40fb31f-53c1-4a2c-8d5f-53501d9c80c3 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs BERTScore: Evaluating Text Generation with BERT

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:33.065454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:33.065454Z digest=sha256:519b8b0fb3acc049896bb7767c1a7172f3129c8032712073a80c515bfc62b077

Observation ce6b19f2-d0d6-4f67-9e0b-574617630a9f · outbound

This paper cites G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:33.070840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:33.070840Z digest=sha256:8f724f751c8bbc88b4f2508548940d58c63dc46ff7556ba97c27451399c64288

Observation 270d5b5a-7212-4f75-8f6a-88f113c7d4fb · outbound

This paper cites Evaluation of geographical distortions in language models,.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Evaluation of geographical distortions in language models,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:33.441938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:33.075843Z digest=sha256:91535e5c71960a840ee5c4c5af0183d2a80b7e8dd4a3e98ec9b6c433e135a4e0

Observation 79eca445-f22b-4295-9ea7-d30b08a2f1a1 · outbound

This paper cites GPT-4 Technical Report.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs GPT-4 Technical Report

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T16:22:33.080354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:22:33.080354Z digest=sha256:53a4d1acb2ed2bfb5aa1c41d871db3e2f7c1fdd7351d777f1de908856d2b1338

Observation cf06014d-cd64-4627-9e39-c1e8908c3970 · outbound

This paper cites Available: https://www.statista.com/statistics/203734/ global-smartphone-penetration-per-capita-since-2005/.

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs Available: https://www.statista.com/statistics/203734/ global-smartphone-penetration-per-capita-since-2005/

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:22:39.091669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:22:32.878816Z digest=sha256:267f02ce91cc025144203c7327dcdeb5ce5e944009cb480fdd2e340907608f65

Pith citing papers

Observation d0791059-4956-4129-a437-79c976a34702 · inbound

Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook cites this paper.

Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs

Reference 139

Resolution
verified exact
arxiv_id, observed 2026-05-13T18:53:08.505234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T18:48:40.813486Z digest=sha256:9308107b7aa34ec0bf2798f5916c79cdd0172f0564fa96f8370b026b12b04eea

Observation 84a39f44-f900-4f7d-8018-1b86f4e6d0a3 · 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 DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-21T06:13:59.496668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T06:09:44.172188Z digest=sha256:56640fce7023e2ddc2f5d5b504d9b868675cb0d11adafb9b00d9c5e8e54239f0