Pith. sign in

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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.873487Z digest=sha256:1ecd9cc0167c6ac655bf569146113d3645f88184ca2809759429de50ef15276b

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.884243Z digest=sha256:79428ca5a6498ed92674200653fa0fbdff6d425fd809a83bee71a9365b220a1d

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.889321Z digest=sha256:48c239e12f70c4acd7d5a0981b3515cf760d27da7fc5610444f7e31f10319d52

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.894134Z digest=sha256:8728f691a2c94a4331856bb8c9624ee5095f727e62dbbdf45e55ad7bcac6c27b

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.904812Z digest=sha256:e82f86b7fe282e007e65a49ed3ade97019938640f790ca5f0fcf0ca0fe0d3551

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.909372Z digest=sha256:795e330689884fa42a9af2b05767b9e19598b107148106b8000e6280252f8826

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.913880Z digest=sha256:b10ea6b30c00c36958b7460d8c900f61d6fdfcba589d7abdb43e2ad23240f1ed

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.918745Z digest=sha256:8e03db99deb954993d4897711fed8740fbc01d9f6ad1172d7b12488eec3bfdd8

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.923186Z digest=sha256:8d9b2afee6975453ddd7b2180587efbe6f612e5c7ab8438ac63b8790ea95669d

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.928086Z digest=sha256:223c6e74693d9d3e81428e27bae4557f6002234cf3a20253e74101283d29732b

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.933097Z digest=sha256:2b965a24ff6aa3c01afba948ab929e9785bc3e89d329016f3cd6b89077e4e3d0

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.947380Z digest=sha256:1151cc45ca933c3a6099b487069918c88966fb83138f3dfeb7fff20d6438253b

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.969360Z digest=sha256:5f0cff965ffcee8ee6087e542aa3c3d9746b691346294273a047081ba2301c59

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.973759Z digest=sha256:2a73a1bd6b9b19316d331c142ed334d012e1a9390a606261fa76ac74d96a0348

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.978103Z digest=sha256:92377639e87a4384f04de037a438b5c6d442affaeb87753f25060c9238138965

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.991024Z digest=sha256:8eb6fe6249c1a077dacf622ad0a9c8a5b8da5f6c727b3575fb0beea3ebf9cc6d

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.995285Z digest=sha256:5101c44a55be0fb4c2b4566f952d69204f069c44469fa00ff432dbd267b54978

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.999793Z digest=sha256:2cd8a7538736da964605848f9fd2de915c8f7be6ff80d00237b6198e5354146f

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.004100Z digest=sha256:10618f22075d0792c9130976e87c865fcc74279168ad4cf5244268838e2715d1

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.008827Z digest=sha256:864ccb179b0576af7e368b6e7bbd652fdedd6b08c92f82f1c8469d98ba26657e

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.014122Z digest=sha256:2433295ffceec965221e79dd9ad3eb734fbd86b654495a5074b9715234016565

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.018809Z digest=sha256:a9a37d1bcba72f7e88d07b65dd3c0cf72880e6e972b12b7642c0be0c1a9931f7

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.024035Z digest=sha256:742fa273e68bb343745cc5d16939bc90be98b3c4b6550219f311b4438bc59f54

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.030044Z digest=sha256:f4d78346964c4a4a7a8a6e01c89868ed6fe29b59553d3f1c9bd68212799cd254

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.035348Z digest=sha256:2d2b4ff3a55a71a729d135b35a32dd3a36e0eb07ea652d6cff3c016d21b67d0a

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.040012Z digest=sha256:ee82029f78c44bb2d5bcda09648fd0871e2fcc1a785aa5c4da39839ec522c8e8

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.044880Z digest=sha256:c33d1cf80de0fd978acd70cfcce1feb79008a0957f91a5d0cf63e1e151f9b1fd

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.049885Z digest=sha256:38b1c7abfcaa5b6d0f9daf719bfe60d77c0af900027e7cda5e10e21cc565a054

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.055299Z digest=sha256:21d1f653ab2e1798c6e55c226993b805fda50a561851acdf12cd30977c4038f0

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.060314Z digest=sha256:8e2d3aa6a32a48d970270e4b942d0f4f5b025d43c4c9a25a03d550657b82be3a

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:33.075843Z digest=sha256:495e8a966889b65bf2ffc07915e77a2df47d1de63eeea55b1f59ca40e3a86b23

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:e7a4944c5890cea38a8c5e44ac15a311c1ad56ebf7c212263a24071c3486590e

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T16:22:32.878816Z digest=sha256:59d6154c059c698dd510780aceb236637ce953d363af5b2e0e1e3dca0c916d35

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-13T18:48:40.813486Z digest=sha256:020cc156b24f0b304e5ce3d70821775f6bdd3d6c2fdef0decc0ff946b05e61a2

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-21T06:09:44.172188Z digest=sha256:22719dc690e7736438e8ec69cc339c586c50debc9ecdf4dfedb361acb3112193