Paper Citation Record · LEDGER

Scaling behavior of large language models in emotional safety classification across sizes and tasks

As of 10 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2509.04512.

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

pith.paper-citation-record.v1
2509.04512 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:25:23.751649Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8ec59f06-d7c9-49bc-9fcd-ab0e3a37e5ca · outbound

This paper cites The digital revolution and its impact on mental health care,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks The digital revolution and its impact on mental health care,

Reference 1

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Observation 0d9a57e1-e4ef-4be0-93e7-f90fcadf2a18 · outbound

This paper cites Digitally assisted mindfulness in training self-regulation skills for sustainable mental health: a systematic review,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Digitally assisted mindfulness in training self-regulation skills for sustainable mental health: a systematic review,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:24.155345Z

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Observation f065d17a-0695-42dc-8abf-66948a3f7d1b · outbound

This paper cites The application of artificial intelligence in the field of mental health: a systematic review,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks The application of artificial intelligence in the field of mental health: a systematic review,

Reference 3

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Observation d40e5002-eab3-4f51-a4d7-de9762d8e238 · outbound

This paper cites Talking to machines about personal mental health problems,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Talking to machines about personal mental health problems,

Reference 4

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Observation 30252ae4-b420-4287-8a2b-5335975462b0 · outbound

This paper cites Mentallama: interpretable mental health analysis on social media with large language models,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Mentallama: interpretable mental health analysis on social media with large language models,

Reference 5

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Observation 4e6417bf-cc2d-499c-a07c-98968ec8e958 · outbound

This paper cites Psy-LLM: Scaling up Global Mental Health Psychological Services with AI-based Large Language Models.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Psy-LLM: Scaling up Global Mental Health Psychological Services with AI-based Large Language Models

Reference 6

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Observation 94554423-d12c-46ec-8c8f-7be52ffd7e57 · outbound

This paper cites Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Reference 7

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Observation 523919ac-ba61-4651-9c75-8a31cf005e75 · outbound

This paper cites Towards safer ai moderation: Evaluating llm moderators through a unified benchmark dataset and advocating a human-first approach,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Towards safer ai moderation: Evaluating llm moderators through a unified benchmark dataset and advocating a human-first approach,

Reference 8

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Observation 471ccf65-e338-495c-a7c6-72a12687a5b8 · outbound

This paper cites Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

Reference 9

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Observation dd6466c5-a3a4-419c-afb5-52a2f4965a5b · outbound

This paper cites SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models.

Scaling behavior of large language models in emotional safety classification across sizes and tasks SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models

Reference 10

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Source-reported events for the cited work

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Observation 36752c81-8368-4663-95c4-f33b58d84364 · outbound

This paper cites Persistent instability in llm’s personality measurements: Effects of scale, reasoning, and conversation history,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Persistent instability in llm’s personality measurements: Effects of scale, reasoning, and conversation history,

Reference 11

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This paper cites Gpt-3.5 technical overview,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Gpt-3.5 technical overview,

Reference 12

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Observation 6291139f-7b28-4112-9c80-df4b62fc82c5 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Scaling behavior of large language models in emotional safety classification across sizes and tasks BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 13

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This paper cites Biobert: a pre-trained biomedical language representation model for biomedical text mining,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Biobert: a pre-trained biomedical language representation model for biomedical text mining,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:24.125998Z

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Observation 1f2c420c-3731-4453-acf6-e1ad4a8fa0fe · outbound

This paper cites When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method.

Scaling behavior of large language models in emotional safety classification across sizes and tasks When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 15

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Observation 03cb6bfb-845a-417c-bc48-89566e8907f6 · outbound

This paper cites A survey on large language model (llm) security and privacy: The good, the bad, and the ugly,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks A survey on large language model (llm) security and privacy: The good, the bad, and the ugly,

Reference 16

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Observation 8bcc55c4-1f3a-4843-ac05-4c992d69a875 · outbound

This paper cites The llama 3 herd of models,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks The llama 3 herd of models,

Reference 17

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Observation c9a6fd5d-1720-4c8e-a4ee-bc02117b5fdb · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Scaling behavior of large language models in emotional safety classification across sizes and tasks LLaMA: Open and Efficient Foundation Language Models

Reference 18

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This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 19

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This paper cites Dreaddit: A Reddit Dataset for Stress Analysis in Social Media.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Dreaddit: A Reddit Dataset for Stress Analysis in Social Media

Reference 20

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This paper cites Identifying depression on reddit: The effect of training data,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Identifying depression on reddit: The effect of training data,

Reference 21

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Observation 606e584e-80f3-4fca-92fa-dd097ff2711d · outbound

This paper cites Sad: A stress anno- tated dataset for recognizing everyday stressors in sms-like conversational systems,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Sad: A stress anno- tated dataset for recognizing everyday stressors in sms-like conversational systems,

Reference 22

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Observation 55ffe0fd-c6ee-44e5-b3a1-a649201e197b · outbound

This paper cites An Annotated Dataset for Explainable Interpersonal Risk Factors of Mental Disturbance in Social Media Posts.

Scaling behavior of large language models in emotional safety classification across sizes and tasks An Annotated Dataset for Explainable Interpersonal Risk Factors of Mental Disturbance in Social Media Posts

Reference 23

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Observation f39284ed-e01d-4f00-b89b-9d4c99d4831e · outbound

This paper cites Multiwd: Multiple wellness dimensions in social media posts,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Multiwd: Multiple wellness dimensions in social media posts,

Reference 24

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Source-reported events for the cited work

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Observation 2cdacbc9-7bb8-40b9-be5d-a08a12edc5c7 · outbound

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

Scaling behavior of large language models in emotional safety classification across sizes and tasks Lora: Low-rank adaptation of large language models

Reference 25

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Source-reported events for the cited work

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Observation 6c8b9616-d42e-455a-88c8-56917c0d4bd5 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Scaling behavior of large language models in emotional safety classification across sizes and tasks DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 26

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Scaling behavior of large language models in emotional safety classification across sizes and tasks Fine-tuning ai models with limited resources,

Reference 27

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Observation d4215a82-bfe9-47ad-b913-465696e84990 · outbound

This paper cites Training language models to follow instructions with human feedback.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Training language models to follow instructions with human feedback

Reference 28

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This paper cites Alpaca: A strong, replicable instruction-following model,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Alpaca: A strong, replicable instruction-following model,

Reference 29

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Observation d16d9128-d55d-4df2-950f-92c18549b5a3 · outbound

This paper cites Transformers reinforcement learning (trl),.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Transformers reinforcement learning (trl),

Reference 30

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Source-reported events for the cited work

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This paper cites Edge-llm: Enabling efficient large language model adaptation on edge devices via unified compression and adaptive layer voting,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Edge-llm: Enabling efficient large language model adaptation on edge devices via unified compression and adaptive layer voting,

Reference 31

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This paper cites Affective intelligence—the missing link?.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Affective intelligence—the missing link?

Reference 32

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Source-reported events for the cited work

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Observation 75ec8d00-d94d-4aee-abab-345e6703b699 · outbound

This paper cites Affect detection: An interdisciplinary review of models, methods, and their applications,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Affect detection: An interdisciplinary review of models, methods, and their applications,

Reference 33

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This paper cites Llm-based edge intelligence: A comprehensive survey on architectures, applications, security and trustwor- thiness,.

Scaling behavior of large language models in emotional safety classification across sizes and tasks Llm-based edge intelligence: A comprehensive survey on architectures, applications, security and trustwor- thiness,

Reference 34

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This paper cites TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices.

Scaling behavior of large language models in emotional safety classification across sizes and tasks TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices

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Scaling behavior of large language models in emotional safety classification across sizes and tasks It should stay grounded in the emotional context of the post and imagine a supportive or healing visual outcome (e.g., recovery, connection, hope)

Reference 36

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Scaling behavior of large language models in emotional safety classification across sizes and tasks me fading into the background

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Scaling behavior of large language models in emotional safety classification across sizes and tasks session_consistent

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Scaling behavior of large language models in emotional safety classification across sizes and tasks "" prompt += f'Post:

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Observation 12ca61c3-bd83-47e0-b1ab-4ccef55f4a4a · outbound

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Scaling behavior of large language models in emotional safety classification across sizes and tasks Unresolved cited work

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Scaling behavior of large language models in emotional safety classification across sizes and tasks "" for example_text, label in few_shot_examples: prompt += f'Post:

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Pith citing papers

No inbound Pith citation observations are available.