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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.873487Z digest=sha256:21e4760629ecbcc1d907cf82452a0dad6d09ec7400473555f598aa7d75b2dc2d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.884243Z digest=sha256:98900713dea75d81f06d3aec69edf4170ddb6a88198ed4398819d4103826e086

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.889321Z digest=sha256:bcee79d75f97c47716f1922279acfbeaac22ccfaa9e70f48e72becfbdda77721

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.894134Z digest=sha256:a3f4db546f3b3b2527e4f1962a9409f14c513b88acbb71de501637789d20eb48

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.904812Z digest=sha256:9107ee3fe18e406754a4edc555ebe911f5a3d63216b5648ea727a34b2c930212

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.909372Z digest=sha256:52949ac57df987e244806b50669e94b42812c35d036c2c9d6adafad78894c80e

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
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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.913880Z digest=sha256:0889362dc60297c14c7c1607eb73c311232a4a136b9bb1caa8a6ac1d322becf3

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.918745Z digest=sha256:b4fb020a0e44b4643e31820cdfd2745cf2c21201a26428bfc6c0e50c7b315340

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
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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.923186Z digest=sha256:3fcec042d8c6bd519bd86cd3e7fdc65569a0e007e61ad8ef67f149a95c103571

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.928086Z digest=sha256:1f8c3cadd718a5300c4bb6bf3f25b9e5ecabb34678663bb4261f7523f2f90a8c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.933097Z digest=sha256:b00c0b31a46fd54493af83444103b3968cee07b435110d038f1bd7314a718f6a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.947380Z digest=sha256:2fcfd2102316ad6dfa995b94e4c6dbdf367603fc1fabf325bb45d88b00db4b4f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.969360Z digest=sha256:1368767effcbe7df543480e38dd6194eff15dda7e3776f2abc5c004b2e1c7e42

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.973759Z digest=sha256:a202991ead7356d2e5f6243f80c84c8b75e1874a24d2685b5f9570b544065866

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.978103Z digest=sha256:34a052df7e911fd43c31f06a223a66c3d51c2d16d53813f77c4003124aceb3d0

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.991024Z digest=sha256:a305746acc598763da36d7637acbc67d40a66352943ced3c2965661b2456c7a4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.995285Z digest=sha256:ae49e66de2d7351e4aaecf1a8674a81b1ed8c7567b895a2941fa1176c77ecdd5

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.999793Z digest=sha256:99123a87889d363ae17a015d0b140832fb9f27abd2c76312124c72a1db3c33ae

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.004100Z digest=sha256:c7b6dd3656e3313464a868be2348f4b60259588b9f506cb1e19ad154d206ff7f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.008827Z digest=sha256:7018da71b3a8c7290e70599907ca087c9df468555f63ba099ba3652465aa7b69

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.014122Z digest=sha256:b8ed132074213b99a307ba885911a704c1f5525d732af0a169efbecb0583f65f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.018809Z digest=sha256:c17275ee7688be58510f060048b2178c73f0108c31a231132da0bb69cefdc4dc

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.024035Z digest=sha256:63d2ba75ce186beb5270f1c6337ffc88c4e42d133a03c2a100091763f619c567

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.030044Z digest=sha256:04feb8c3bb6b7f2967a3f7ae9aa043f3d94bba3984e9c4702c5e83e497711723

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.035348Z digest=sha256:3f8e6db921842c64dea054afd9e71f85d14416901efc212a88d7f8c8de529561

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.040012Z digest=sha256:0fbfb48e390af68524b258b695cb7f951550f0c6a451ed0728c03e8cf47b3268

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.044880Z digest=sha256:e2a2cb0d4e0876faac70b844620fa382e7316e8464ac246cf0138689e4abf715

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.049885Z digest=sha256:bc88efc8eed75ecbb8d725d8283da5154153af66000135169d1bdfd2a409bb68

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.055299Z digest=sha256:20a114b507519f310aeb70ebadb56d5fd4e80036d7510ff67c8bf3b23f1c154e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.060314Z digest=sha256:1dc7a6fa1277629d581ebf71f32540adfed3d04a8806b745dfb379b4c75b7c97

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.

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:33.075843Z digest=sha256:cebb4eeb5edde6549fa85785bdb971fee15eda04f951fddb9220b60a9bba158b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:22:32.878816Z digest=sha256:cccc72b6d165b8b0aeedd9aa11b05770996b8d676fbc1609a0560965472bfe5d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T18:48:40.813486Z digest=sha256:a1ac0d6cc1409995c1b9b5a609209c9185ec8e72b624a000b0d9d284d346a3df

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T06:09:44.172188Z digest=sha256:03980fb4a92712bbe6fc4c6d149429c8dceb5ef950519315f9cb96f5ecf9742e