GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing | Paper Citation Record

Observation a8df3088-0638-47d8-a777-e059dad81c49 · outbound

This paper cites Sensing technologies for monitoring serious mental illnesses.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Sensing technologies for monitoring serious mental illnesses

Reference 1

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Observation ff9ccfb1-6f38-4010-b3c7-01c264ec2005 · outbound

This paper cites Adler, Yuewen Yang, Thalia Viranda, Xuhai Xu, David C.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Adler, Yuewen Yang, Thalia Viranda, Xuhai Xu, David C

Reference 2

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Observation 7bfecf95-3745-413c-9a75-3cba9d2c4ad1 · outbound

This paper cites Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation

Reference 3

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Observation e60fab9d-536e-4846-9ee7-187ea025128b · outbound

This paper cites Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect

Reference 4

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Observation f33d6346-f9ed-4d72-b5ec-b77eda8a6b52 · outbound

This paper cites Frustrated and confused: the American public rates its cancer-related information-seeking experiences.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Frustrated and confused: the American public rates its cancer-related information-seeking experiences

Reference 5

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Observation b854fe08-3ac1-4cb6-a204-c156707d2e34 · outbound

This paper cites Abandonment of personal quantification: A review and empirical study investigating reasons for wearable activity tracking attrition.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Abandonment of personal quantification: A review and empirical study investigating reasons for wearable activity tracking attrition

Reference 6

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Observation a4776806-cf2c-4e3e-a30b-5c9e64fab299 · outbound

This paper cites an unresolved cited work.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Unresolved cited work

Reference 7

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Observation e7ade742-87c8-4f2b-937e-1c6307cdc520 · outbound

This paper cites The interpretation and exploitation of information in criminal investigations.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing The interpretation and exploitation of information in criminal investigations

Reference 8

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Observation c65aa4ce-d667-444a-9d11-831cb6d7c476 · outbound

This paper cites Reviewing reflection: on the use of reflection in interactive system design.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Reviewing reflection: on the use of reflection in interactive system design

Reference 9

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Observation ee2b0c2f-5c0d-49c0-adc8-3a6dd3bb2c7a · outbound

This paper cites Revisiting reflection in hci: Four design resources for technologies that support reflection.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Revisiting reflection in hci: Four design resources for technologies that support reflection

Reference 10

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Observation f6ab3fc7-d88a-4820-a7f2-694f5215d256 · outbound

This paper cites Detecting stress in college freshman from wearable sleep data.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Detecting stress in college freshman from wearable sleep data

Reference 11

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Observation 77d4b645-48ff-4f4c-9eb0-c1144e8fd84f · outbound

This paper cites Go and grow: Mapping personal data to a living plant.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Go and grow: Mapping personal data to a living plant

Reference 12

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Observation 79990db9-a45c-42a4-b223-3a48b256e201 · outbound

This paper cites Patient engagement in a multimodal digital phenotyping study of opioid use disorder.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Patient engagement in a multimodal digital phenotyping study of opioid use disorder

Reference 13

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Observation cda88c02-3a89-4cdd-84ac-e9f4ce46173a · outbound

This paper cites Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness

Reference 14

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Observation f7d691c1-53f7-4ba8-9906-a07f7a1fd12f · outbound

This paper cites Methods in predictive techniques for mental health status on social media: a critical review.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Methods in predictive techniques for mental health status on social media: a critical review

Reference 15

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Observation 1d46ea81-0564-4b32-ac9d-787b18154e28 · outbound

This paper cites Sensor2Text: Enabling natural language interactions for daily activity tracking using wearable sensors.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Sensor2Text: Enabling natural language interactions for daily activity tracking using wearable sensors

Reference 16

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Observation 93f12ee6-1f71-473d-840d-cb6f64798b72 · outbound

This paper cites Understanding client support strategies to improve clinical outcomes in an online mental health intervention.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Understanding client support strategies to improve clinical outcomes in an online mental health intervention

Reference 17

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Observation 55e493a8-2afa-4e14-9d13-6e0f4cd1bdb2 · outbound

This paper cites Understanding quantified-selfers’ practices in collecting and exploring personal data.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Understanding quantified-selfers’ practices in collecting and exploring personal data

Reference 18

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Observation 20acb125-b1c2-4bdf-88e6-90e50cfbe4da · outbound

This paper cites Imputation Matters: A Deeper Look into an Overlooked Step in Longitudinal Health and Behavior Sensing Research.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Imputation Matters: A Deeper Look into an Overlooked Step in Longitudinal Health and Behavior Sensing Research

Reference 19

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Observation 4474c9f6-8d4d-4d24-b3b3-1dd619bec872 · outbound

This paper cites SeSaMe: A Framework to Simulate Self-Reported Ground Truth for Mental Health Sensing Studies.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing SeSaMe: A Framework to Simulate Self-Reported Ground Truth for Mental Health Sensing Studies

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:29:16.278605Z

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Observation 3830d9ac-89af-41d0-8275-e8bce5947cff · outbound

This paper cites Health information needs, sources, and barriers of primary care patients to achieve patient-centered care: A literature review.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Health information needs, sources, and barriers of primary care patients to achieve patient-centered care: A literature review

Reference 21

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Observation fae8c770-8289-463c-9159-f433c8c7d6fd · outbound

This paper cites Grounded theory research: Procedures, canons, and evaluative criteria.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Grounded theory research: Procedures, canons, and evaluative criteria

Reference 22

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Observation 46799a91-ff2c-42bd-9ba0-8b79344ad609 · outbound

This paper cites Towards a Personal Health Large Language Model.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Towards a Personal Health Large Language Model

Reference 23

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Observation b4b764c0-e1be-4648-8cb9-c7cfc2b5fb85 · outbound

This paper cites Data sensemaking in self-tracking: Towards a new generation of self-tracking tools.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Data sensemaking in self-tracking: Towards a new generation of self-tracking tools

Reference 24

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Observation 02c3b391-3f42-415f-bf9d-db5deeaa175e · outbound

This paper cites Semantic gap in predicting mental wellbeing through passive sensing.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Semantic gap in predicting mental wellbeing through passive sensing

Reference 25

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Observation bba7b7eb-c751-4508-bcc1-e98f743dd413 · outbound

This paper cites Benchmarks for automated commonsense reasoning: A survey.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Benchmarks for automated commonsense reasoning: A survey

Reference 26

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Observation ccb71933-5587-4001-982c-ab2915d39738 · outbound

This paper cites Predicting depression via social media.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Predicting depression via social media

Reference 27

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Observation 37152a4e-cb4e-47e3-8f90-7d6a9515574c · outbound

This paper cites From the mind’s eye of the “user”: The sense-making qualitative-quantitative methodology.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing From the mind’s eye of the “user”: The sense-making qualitative-quantitative methodology

Reference 28

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Observation 622ca119-2794-4a5e-a3a9-ea7221e54f8d · outbound

This paper cites An overview of sense-making research: Concepts, methods, and results to date.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing An overview of sense-making research: Concepts, methods, and results to date

Reference 29

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Observation 10d7b13f-9a51-43d2-be99-01a11ca68914 · outbound

This paper cites The role of feedback in the process of health behavior change.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing The role of feedback in the process of health behavior change

Reference 30

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Observation d7e2469a-4e96-4b06-b8ce-e1d3999b6ded · outbound

This paper cites Deep neural networks in psychiatry.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Deep neural networks in psychiatry

Reference 31

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Observation f5b4fb3c-37dc-4e6e-a9f5-e8f53d310095 · outbound

This paper cites Imputation of missing longitudinal data: a comparison of methods.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Imputation of missing longitudinal data: a comparison of methods

Reference 32

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This paper cites Epstein, Clara Caldeira, Mayara Costa Figueiredo, Xi Lu, Lucas M.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Epstein, Clara Caldeira, Mayara Costa Figueiredo, Xi Lu, Lucas M

Reference 33

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Observation f253a6c5-83f6-45e6-a6c1-1159290c5260 · outbound

This paper cites PhysioLLM: Supporting Personalized Health Insights with Wearables and Large Language Models.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing PhysioLLM: Supporting Personalized Health Insights with Wearables and Large Language Models

Reference 34

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Observation ad09be52-6e4b-4338-b40f-0e17bb719510 · outbound

This paper cites Mobile sensing for behavioral research: A component-based approach for rapid deployment of sensing campaigns.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Mobile sensing for behavioral research: A component-based approach for rapid deployment of sensing campaigns

Reference 35

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Observation e00de5ef-3daa-4fe3-b1ed-7e8e9993e5e7 · outbound

This paper cites Blue versus gray: A metaphor constraining sensemaking around a restructuring.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Blue versus gray: A metaphor constraining sensemaking around a restructuring

Reference 36

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This paper cites Fostering engagement with personal informatics systems.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Fostering engagement with personal informatics systems

Reference 37

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This paper cites Describing the elephant: a foundational model of human needs, motivation, behaviour, and wellbeing, December 2020.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Describing the elephant: a foundational model of human needs, motivation, behaviour, and wellbeing, December 2020

Reference 38

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Observation 0c281b4d-ec4f-4244-8fa8-677136fca2b0 · outbound

This paper cites Systematic Evaluation of Personalized Deep Learning Models for Affect Recognition.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Systematic Evaluation of Personalized Deep Learning Models for Affect Recognition

Reference 39

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This paper cites Design of digital workplace stress-reduction intervention systems: Effects of intervention type and timing.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Design of digital workplace stress-reduction intervention systems: Effects of intervention type and timing

Reference 40

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Observation 43cf6931-f1cb-449a-b0ce-d8e9db0def6f · outbound

This paper cites Large Language Models in Mental Health Care: a Scoping Review.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Large Language Models in Mental Health Care: a Scoping Review

Reference 41

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This paper cites Insufficient effort responding: examining an insidious confound in survey data.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Insufficient effort responding: examining an insidious confound in survey data

Reference 42

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Observation 2383c641-d17c-45e4-a87b-23ac8c5406e2 · outbound

This paper cites Jacobson, Damien Lekkas, Raphael Huang, and Natalie Thomas.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Jacobson, Damien Lekkas, Raphael Huang, and Natalie Thomas

Reference 43

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Observation 5060ae55-1186-42fe-9505-58b07dacae97 · outbound

This paper cites Multimodal Autoencoder: A Deep Learning Approach to Filling In Missing Sensor Data and Enabling Better Mood Prediction.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Multimodal Autoencoder: A Deep Learning Approach to Filling In Missing Sensor Data and Enabling Better Mood Prediction

Reference 44

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Observation d88bf7b9-a372-4a9c-928c-42939581dc98 · outbound

This paper cites HARGPT: Are LLMs Zero-Shot Human Activity Recognizers? pages 38–43.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing HARGPT: Are LLMs Zero-Shot Human Activity Recognizers? pages 38–43

Reference 45

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Observation 2f10ea1a-0a06-42de-9df6-739231e45571 · outbound

This paper cites DT2VIS: A Focus+Context Answer Generation System to Facilitate Visual Exploration of Tabular Data.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing DT2VIS: A Focus+Context Answer Generation System to Facilitate Visual Exploration of Tabular Data

Reference 46

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Observation c329b21b-68c7-4c77-8625-4eecde90086e · outbound

This paper cites Designing for data sensemaking practices: a complex challenge.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Designing for data sensemaking practices: a complex challenge

Reference 47

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Observation 4a6fde6d-0385-4c7c-ae59-0689933a3ea3 · outbound

This paper cites Drawbacks of artificial intelligence and their potential solutions in the healthcare sector.Biomedical Materials & Devices, 1(2):731–738, 2023.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Drawbacks of artificial intelligence and their potential solutions in the healthcare sector.Biomedical Materials & Devices, 1(2):731–738, 2023

Reference 48

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Observation ecc395d8-f61b-42a6-9cdd-b9d43ccc1f4d · outbound

This paper cites Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Data.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Data

Reference 49

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This paper cites A data–frame theory of sensemaking.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing A data–frame theory of sensemaking

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:29.878412Z

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Observation e1633150-31e2-4335-98e7-731af1bc4ac7 · outbound

This paper cites Intelligence essentials for everyone.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Intelligence essentials for everyone

Reference 51

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Observation fa7ddbc5-cfc0-47fe-ae69-608ec92e663d · outbound

This paper cites Properties and Challenges of LLM-Generated Explanations.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Properties and Challenges of LLM-Generated Explanations

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:29:15.874768Z

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Observation b00759b7-4790-4241-a886-b66e40d1a1f7 · outbound

This paper cites Why we use and abandon smart devices.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Why we use and abandon smart devices

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:29.273432Z

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.

Observation a4eac62c-2135-4052-9cef-74283709bef9 · outbound

This paper cites Collecting self-reported physical activity and posture data using audio-based ecological momentary assessment.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Collecting self-reported physical activity and posture data using audio-based ecological momentary assessment

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:28.984356Z

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.

Observation d633165f-7cd8-42f2-9d13-a0afcfacd279 · outbound

This paper cites Feasibility and Utility of Multimodal Micro Ecological Momentary Assessment on a Smartwatch.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Feasibility and Utility of Multimodal Micro Ecological Momentary Assessment on a Smartwatch

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:28.679221Z

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.

Observation a3abffeb-5a18-4eb4-804d-b7549e3aa604 · outbound

This paper cites Learning to Reduce: Optimal Representations of Structured Data in Prompting Large Language Models.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Learning to Reduce: Optimal Representations of Structured Data in Prompting Large Language Models

Reference 56

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T19:29:15.670517Z

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.

Observation 97890645-6f1c-48e9-87de-6d2bff9998dc · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Retrieval-augmented generation for knowledge-intensive NLP tasks

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:28.382007Z

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.

Observation 2e6e88e6-5dd5-4aca-b493-0ff801b5e188 · outbound

This paper cites Solving Quantitative Reasoning Problems with Language Models.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Solving Quantitative Reasoning Problems with Language Models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:28.071112Z

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.

Observation 3e9ba52b-30d0-4f71-b748-b07c01ab9c79 · outbound

This paper cites A stage-based model of personal informatics systems.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing A stage-based model of personal informatics systems

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:27.842578Z

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.

Observation 1ea880dd-4912-421a-b960-da4b89f0f3ee · outbound

This paper cites Understanding my data, myself: supporting self-reflection with ubicomp technologies.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Understanding my data, myself: supporting self-reflection with ubicomp technologies

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:27.592525Z

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.

Observation 0395de6e-a083-4932-b04e-efd952dd8c6f · outbound

This paper cites Vital insight: Assisting experts’ sensemaking process of multi-modal personal tracking data using visualization and LLM.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Vital insight: Assisting experts’ sensemaking process of multi-modal personal tracking data using visualization and LLM

Reference 61

Resolution: verified exact; raw_fallback, observed 2026-08-06T19:29:15.451357Z

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.

Observation b9e22c1d-9221-484b-8291-2df4e9a77ad5 · outbound

This paper cites StarCoder: may the source be with you!.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing StarCoder: may the source be with you!

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T19:29:08.090179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6e158f8-5bdb-4a9a-a682-fb67e4af6226 · outbound

This paper cites Just-in-time but not too much: Determining treatment timing in mobile health.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, 2(4):1–21, 2018.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Just-in-time but not too much: Determining treatment timing in mobile health.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, 2(4):1–21, 2018

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:27.333233Z

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.

Observation bc7d7edb-cb9e-4d6b-97d4-ec0a24812a98 · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing StarCoder 2 and The Stack v2: The Next Generation

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-06T19:29:08.398352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0de89a4d-b030-4761-83e9-8eb415268fae · outbound

This paper cites Joint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Joint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:27.056210Z

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.

Observation 06eb69dc-0ae0-462e-8ea5-4471e1932693 · outbound

This paper cites Breathing as Input Modality in a Gameful Breathing Training App: Development and Evaluation of Breeze 2 (Preprint).

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Breathing as Input Modality in a Gameful Breathing Training App: Development and Evaluation of Breeze 2 (Preprint)

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:26.848604Z

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.

Observation 4dc3b957-8e30-4e46-a194-a2c86d973cc0 · outbound

This paper cites Accessible visualization via natural language descriptions: A four-level model of semantic content.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Accessible visualization via natural language descriptions: A four-level model of semantic content

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:26.548924Z

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.

Observation 1a5e5ae0-f2b1-4fe6-8a27-1cb09e07dd43 · outbound

This paper cites Language Models of Code are Few-Shot Commonsense Learners.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Language Models of Code are Few-Shot Commonsense Learners

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-06T19:29:08.828226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7697096c-6134-4ea9-b40e-5998b22609e5 · outbound

This paper cites Personal discovery in diabetes self-management: discovering cause and effect using self-monitoring data.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Personal discovery in diabetes self-management: discovering cause and effect using self-monitoring data

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:26.265411Z

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.

Observation 8fc2efa7-e1fc-422b-a9e0-685b1fb5d075 · outbound

This paper cites Transforming Wearable Data into Personal Health Insights using Large Language Model Agents.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Transforming Wearable Data into Personal Health Insights using Large Language Model Agents

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-06T19:29:09.104517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f31cc297-6a43-4599-b4da-d8ac4e1fb767 · outbound

This paper cites Walter, Marion J.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Walter, Marion J

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:26.023760Z

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.

Observation 22437162-d72f-4f14-b63c-c27dffbcd875 · outbound

This paper cites Detecting receptivity for mHealth interventions in the natural environment.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Detecting receptivity for mHealth interventions in the natural environment

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:25.696556Z

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.

Observation c5cded9e-c973-48db-8ae1-6a4a1bc7632c · outbound

This paper cites Continuous Detection of Physiological Stress with Commodity Hardware.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Continuous Detection of Physiological Stress with Commodity Hardware

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:25.196465Z

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.

Observation 41725bb3-94d8-45b9-9056-88561bf7e751 · outbound

This paper cites Evaluating the reproducibility of physiological stress detection models.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Evaluating the reproducibility of physiological stress detection models

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:24.945486Z

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.

Observation ccbb41bb-f078-4af2-a7ef-b66127bdafaa · outbound

This paper cites Personal sensing: understanding mental health using ubiquitous sensors and machine learning.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Personal sensing: understanding mental health using ubiquitous sensors and machine learning

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:24.763057Z

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.

Observation e6d95c0e-a434-4ebc-889c-adca42b106dd · outbound

This paper cites Momentary stressor logging and reflective visualizations: Implications for stress management with wearables.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Momentary stressor logging and reflective visualizations: Implications for stress management with wearables

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:24.534552Z

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.

Observation bef3f24d-8695-44ad-b629-12ee492f7b4a · outbound

This paper cites Supporting meaningful personal fitness: The tracker goal evolution model.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Supporting meaningful personal fitness: The tracker goal evolution model

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:24.308057Z

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.

Observation 71296cfa-3c58-44fd-af16-5a35a1f67890 · outbound

This paper cites On the role of active memory processes in perception and cognition.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing On the role of active memory processes in perception and cognition

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:24.101724Z

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.

Observation 53def9f8-ba2f-40a0-b53d-acdb2008e58a · outbound

This paper cites OpenAI documentation: Prompt engineering.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing OpenAI documentation: Prompt engineering

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:23.876936Z

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.

Observation 248b3999-eb81-40a1-8282-66421dd564a6 · outbound

This paper cites GPT-4o System Card.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing GPT-4o System Card

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T19:29:10.482642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f60ad168-401c-4be2-84a6-f4970ea997bc · outbound

This paper cites LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T19:29:10.583062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03b476f6-7f4a-45a9-887b-a596afff6e6f · outbound

This paper cites The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:23.643091Z

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.

Observation 6ce90121-bcd0-4786-98df-2ccecbd71fda · outbound

This paper cites Behavioral indicators on a mobile sensing platform predict clinically validated psychiatric symptoms of mood and anxiety disorders.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Behavioral indicators on a mobile sensing platform predict clinically validated psychiatric symptoms of mood and anxiety disorders

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:23.385955Z

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.

Observation e2ca4b6a-a318-497f-b7fb-ca8646e39067 · outbound

This paper cites Clear, and Peter Wright.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Clear, and Peter Wright

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:23.103065Z

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.

Observation 39f18271-ca84-4fbb-9514-1e8ba21a90fc · outbound

This paper cites Building shared understanding in collaborative sensemaking.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Building shared understanding in collaborative sensemaking

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:22.750867Z

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.

Observation 44216c0e-95a0-4e23-a162-d19c5295fed4 · outbound

This paper cites Lee, Ashley Garrity, and Mark W.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Lee, Ashley Garrity, and Mark W

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:22.525498Z

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.

Observation f231eee0-715c-44e7-8f2c-a93cf68f8b00 · outbound

This paper cites CataractBot: An LLM-Powered Expert-in-the-Loop Chatbot for Cataract Patients.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing CataractBot: An LLM-Powered Expert-in-the-Loop Chatbot for Cataract Patients

Reference 87

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:29:14.780432Z

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.

Observation 903c0245-abc1-4902-95b8-8bc4d7dd4c70 · outbound

This paper cites Personal tracking as lived informatics.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Personal tracking as lived informatics

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:22.317920Z

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.

Observation 684b4b25-f7a1-4288-96a2-15a6ee2c6d8b · outbound

This paper cites The cost structure of sensemaking.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing The cost structure of sensemaking

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:22.065608Z

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.

Observation 07493812-338c-44c2-b9d0-24766d464038 · outbound

This paper cites Stress recognition using wearable sensors and mobile phones.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Stress recognition using wearable sensors and mobile phones

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:21.749498Z

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.

Observation 9108700e-9620-4ac6-84d7-9a87c7f37cb8 · outbound

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

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Introducing WESAD, a multimodal dataset for wearable stress and affect detection

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:21.496034Z

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.

Observation 383932e6-9766-4257-89e7-4c04df0ecd7b · outbound

This paper cites Ecological momentary assessment.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Ecological momentary assessment

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:21.146083Z

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.

Observation c3adb5b3-cc33-4668-9c1b-303c48d39112 · outbound

This paper cites Towards Expert-Level Medical Question Answering with Large Language Models.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Towards Expert-Level Medical Question Answering with Large Language Models

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-06T19:29:11.999241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c897e87-aa4f-4dbc-9d1f-bec3853c8fa9 · outbound

This paper cites Narrating fitness: Leveraging large language models for reflective fitness tracker data interpretation.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Narrating fitness: Leveraging large language models for reflective fitness tracker data interpretation

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:20.841625Z

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.

Observation 38426dd7-5c7c-4645-9878-f87233b85271 · outbound

This paper cites Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:20.543667Z

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.

Observation 6750e798-d9c9-42f5-bff7-c8b2bd206989 · outbound

This paper cites DepreST-CAT: Retrospective smartphone call and text logs collected during the covid-19 pandemic to screen for mental illnesses.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing DepreST-CAT: Retrospective smartphone call and text logs collected during the covid-19 pandemic to screen for mental illnesses

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:20.212049Z

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.

Observation 1241a45a-a2db-4b8e-a7aa-7b2977fa1606 · outbound

This paper cites Language Models Don’t Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Language Models Don’t Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:19.960908Z

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.

Observation c9cc82af-a3fd-4f9f-809c-3100e8fae184 · outbound

This paper cites Design factors of longitudinal smartphone-based health surveys.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Design factors of longitudinal smartphone-based health surveys

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:19.738997Z

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.

Observation 6f864600-1fd7-4f61-a45d-1e982b9ebb17 · outbound

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

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing StudentLife: Assessing mental health, academic performance and behavioral trends of college students using smartphones

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:19.493694Z

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.

Observation 29ad4dea-e4e3-452c-8093-60c1d02dff43 · outbound

This paper cites Towards Natural Language-Based Visualization Authoring.

GLOSS: Group of LLMs for Open-Ended Sensemaking of Passive Sensing Data for Health and Wellbeing Towards Natural Language-Based Visualization Authoring

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:29:19.275197Z

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.

Coverage vector

Reference resolution

Outbound references

Pith citing papers