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  1. Home
  2. /Repositories
  3. /Emo-gml/Awesome-Mental-Health-LLMs
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago

Emo-gml/Awesome-Mental-Health-LLMs

From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health (TAFFC)

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 64%Team MKC at CLPsych 2026: Capturing and Characterizing Mental Health Changes through Social Media Timeline Dynamics →
  • PossiblePossibly related (embedding) · 57%Towards AI-augmented decision making in psychiatry →
  • PossiblePossibly related (embedding) · 53%RSPC: A Benchmark for Modeling Stress and Psychiatric Conditions in Digitally Mediated Relationships using Psychiatrist Annotations →
  • PossiblePossibly related (embedding) · 52%Identifying Interactions at Scale for LLMs →
  • PossiblePossibly related (embedding) · 51%SPLIT: Cross-Lingual Empathy and Cultural Grounding in English and Ukrainian LLM Responses →
  • PossiblePossibly related (embedding) · 54%Large language models exhibit stigmatizing behaviour in contextual judgements of health conditions - Nature →
  • PossiblePossibly related (embedding) · 50%Multi-Large Language Model Orchestrated Severity Assessment of Clinical Records (MOSAIC) →
  • PossiblePossibly related (embedding) · 53%Benchmarking large language models against practicing clinicians on psychopathological assessment - Nature →

Implements

paperTeam MKC at CLPsych 2026: Capturing and Characterizing Mental Health Changes through Social Media Timeline DynamicspaperRSPC: A Benchmark for Modeling Stress and Psychiatric Conditions in Digitally Mediated Relationships using Psychiatrist AnnotationspaperSPLIT: Cross-Lingual Empathy and Cultural Grounding in English and Ukrainian LLM Responses

Covers

newsTowards AI-augmented decision making in psychiatrynewsIdentifying Interactions at Scale for LLMs

Covers (incoming)

newsLarge language models exhibit stigmatizing behaviour in contextual judgements of health conditions - NaturenewsBenchmarking large language models against practicing clinicians on psychopathological assessment - NaturenewsSmall language models in medicine - NaturenewsLarge language models for interpretation of health checkup results - Nature

Implements (incoming)

paperMulti-Large Language Model Orchestrated Severity Assessment of Clinical Records (MOSAIC)paperCreativity, honesty and designed forgetting emerge in small hyperbolic language models

Related across the graph

paperTeam MKC at CLPsych 2026: Capturing and Characterizing Mental Health Changes through Social Media Timeline DynamicsnewsBenchmarking large language models against practicing clinicians on psychopathological assessment - NaturepaperCreativity, honesty and designed forgetting emerge in small hyperbolic language modelsnewsLarge language models exhibit stigmatizing behaviour in contextual judgements of health conditions - NaturenewsTowards AI-augmented decision making in psychiatrynewsLarge language models for interpretation of health checkup results - NaturepaperMulti-Large Language Model Orchestrated Severity Assessment of Clinical Records (MOSAIC)newsSmall language models in medicine - NaturepaperRSPC: A Benchmark for Modeling Stress and Psychiatric Conditions in Digitally Mediated Relationships using Psychiatrist AnnotationsnewsIdentifying Interactions at Scale for LLMspaperSPLIT: Cross-Lingual Empathy and Cultural Grounding in English and Ukrainian LLM Responses
Knowledge path·PTeam MKC at CLPsych 2026: Capturing and Characterizing Mental Health Changes through Social Media Timeline Dynamics→NBenchmarking large language models against practicing clinicians on psychopathological assessment - Nature→PCreativity, honesty and designed forgetting emerge in small hyperbolic language models→REmo-gml/Awesome-Mental-Health-LLMs

Topics

agentemotionllmmental-healthpsychologysurvey

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Graph trust82Primary
Graph score104