mlsanityData to 14 Oct 2026

Breaking the Stigma! Unobtrusively Probe Symptoms in Depression Disorder Diagnosis Dialogue

arXiv 2501.15260 ↗First posted 25 Jan 2025cs.CL cs.CYcited by 2

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Abstract (arXiv)

Stigma has emerged as one of the major obstacles to effectively diagnosing depression, as it prevents users from open conversations about their struggles. This requires advanced questioning skills to carefully probe the presence of specific symptoms in an unobtrusive manner. While recent efforts have been made on depression-diagnosis-oriented dialogue systems, they largely ignore this problem, ultimately hampering their practical utility. To this end, we propose a novel and effective method, UPSD4, developing a series of strategies to promote a sense of unobtrusiveness within the dialogue system and assessing depression disorder by probing symptoms. We experimentally show that UPSD4 demonstrates a significant improvement over current baselines, including unobtrusiveness evaluation of dialogue content and diagnostic accuracy. We believe our work contributes to developing more accessible and user-friendly tools for addressing the widespread need for depression diagnosis.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 13 of its 55 references that are in the map. First posted on arXiv 25 Jan 2025.

Builds on

13 of 55 references.

References · 13

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
  3. 2016A Network-based End-to-End Trainable Task-oriented Dialogue Systemcited by 252
  4. 2023Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaborationcited by 116
  5. 2021CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generationcited by 81
  6. 2020Adding Chit-Chat to Enhance Task-Oriented Dialoguescited by 48
  7. 2022D4: a Chinese Dialogue Dataset for Depression-Diagnosis-Oriented Chatcited by 37
  8. 2021OTTers: One-turn Topic Transitions for Open-Domain Dialoguecited by 29
  9. 2023Revisit Input Perturbation Problems for LLMs: A Unified Robustness Evaluation Framework for Noisy Slot Filling Taskcited by 23
  10. 2021TIAGE: A Benchmark for Topic-Shift Aware Dialog Modelingcited by 22
  11. 2023S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMscited by 7
  12. 2024Towards Reliable and Empathetic Depression-Diagnosis-Oriented Chatscited by 3
1 more
  1. 2024Enhancing Depression-Diagnosis-Oriented Chat with Psychological State Trackingcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.