Cover Image

Your Model Is Not Predicting Depression Well And That Is Why: A Case Study of PRIMATE Dataset

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Milintsevich, Kirill, Sirts, Kairit, Dias, Gaël
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Evaluating Lexicon Incorporation for Depression Symptom Estimation
by: Milintsevich, Kirill, et al.
Published: (2024)

Context is Important in Depressive Language: A Study of the Interaction Between the Sentiments and Linguistic Markers in Reddit Discussions
by: Sharma, Neha, et al.
Published: (2024)

Comparison of Current Approaches to Lemmatization: A Case Study in Estonian
by: Dorkin, Aleksei, et al.
Published: (2024)

Exploratory Study into Relations between Cognitive Distortions and Emotional Appraisals
by: Agarwal, Navneet, et al.
Published: (2025)

Sõnajaht: Definition Embeddings and Semantic Search for Reverse Dictionary Creation
by: Dorkin, Aleksei, et al.
Published: (2024)

TartuNLP @ SIGTYP 2024 Shared Task: Adapting XLM-RoBERTa for Ancient and Historical Languages
by: Dorkin, Aleksei, et al.
Published: (2024)

TartuNLP @ AXOLOTL-24: Leveraging Classifier Output for New Sense Detection in Lexical Semantics
by: Dorkin, Aleksei, et al.
Published: (2024)

TartuNLP at EvaLatin 2024: Emotion Polarity Detection
by: Dorkin, Aleksei, et al.
Published: (2024)

GliLem: Leveraging GliNER for Contextualized Lemmatization in Estonian
by: Dorkin, Aleksei, et al.
Published: (2024)

TartuNLP at SemEval-2025 Task 5: Subject Tagging as Two-Stage Information Retrieval
by: Dorkin, Aleksei, et al.
Published: (2025)

Exploring Profiles of Cognitive Distortions Associated with Mental Health Disorders
by: Anikejeva, Alina, et al.
Published: (2026)

Creation of the Estonian Subjectivity Dataset: Assessing the Degree of Subjectivity on a Scale
by: Gailit, Karl Gustav, et al.
Published: (2025)

Prune or Retrain: Optimizing the Vocabulary of Multilingual Models for Estonian
by: Dorkin, Aleksei, et al.
Published: (2025)

Assessing the Reliability and Validity of GPT-4 in Annotating Emotion Appraisal Ratings
by: Ruder, Deniss, et al.
Published: (2025)

Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Translation
by: Ojastu, Marii, et al.
Published: (2025)

EstLLM: Enhancing Estonian Capabilities in Multilingual LLMs via Continued Pretraining and Post-Training
by: Dorkin, Aleksei, et al.
Published: (2026)

Datasets for Depression Modeling in Social Media: An Overview
by: Bucur, Ana-Maria, et al.
Published: (2025)

LLaMAX2: Your Translation-Enhanced Model also Performs Well in Reasoning
by: Gao, Changjiang, et al.
Published: (2025)

CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysis
by: Xu, Jinyuan, et al.
Published: (2025)

What is the Role of Small Models in the LLM Era: A Survey
by: Chen, Lihu, et al.
Published: (2024)

Not All Correct Answers Are Equal: Why Your Distillation Source Matters
by: Tian, Xiaoyu, et al.
Published: (2025)

Why is Your Language Model a Poor Implicit Reward Model?
by: Razin, Noam, et al.
Published: (2025)

Semantic Gravity Wells: Why Negative Constraints Backfire
by: Rana, Shailesh
Published: (2026)

Exploring Social Media Posts for Depression Identification: A Study on Reddit Dataset
by: Harshit, Nandigramam Sai, et al.
Published: (2024)

Convomem Benchmark: Why Your First 150 Conversations Don't Need RAG
by: Pakhomov, Egor, et al.
Published: (2025)

Assessing ML Classification Algorithms and NLP Techniques for Depression Detection: An Experimental Case Study
by: Lorenzoni, Giuliano, et al.
Published: (2024)

Depression and Anxiety Prediction Using Deep Language Models and Transfer Learning
by: Rutowski, Tomasz, et al.
Published: (2024)

ReDSM5: A Reddit Dataset for DSM-5 Depression Detection
by: Bao, Eliseo, et al.
Published: (2025)

Positioning Political Texts with Large Language Models by Asking and Averaging
by: Mens, Gaël Le, et al.
Published: (2023)

CommonWhy: A Dataset for Evaluating Entity-Based Causal Commonsense Reasoning in Large Language Models
by: Toroghi, Armin, et al.
Published: (2026)

Predicting Through Generation: Why Generation Is Better for Prediction
by: Kowsher, Md, et al.
Published: (2025)

CASCADE Your Datasets for Cross-Mode Knowledge Retrieval of Language Models
by: Zhou, Runlong, et al.
Published: (2025)

BPQA Dataset: Evaluating How Well Language Models Leverage Blood Pressures to Answer Biomedical Questions
by: Hang, Chi, et al.
Published: (2025)

The Case for Evaluating Multimodal Translation Models on Text Datasets
by: Vijayan, Vipin, et al.
Published: (2024)

A Gold Standard Dataset and Evaluation Framework for Depression Detection and Explanation in Social Media using LLMs
by: Bolegave, Prajval, et al.
Published: (2025)

A Comparative Analysis of Machine Learning and Deep Learning Models for Tweet Sentiment Classification: A Case Study on the Sentiment140 Dataset
by: Anggraini, Vita, et al.
Published: (2026)

How Well Do LLMs Understand Drug Mechanisms? A Knowledge + Reasoning Evaluation Dataset
by: Mohan, Sunil, et al.
Published: (2025)

Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation
by: Gendron, Barbara, et al.
Published: (2024)

Efficiently Identifying Low-Quality Language Subsets in Multilingual Datasets: A Case Study on a Large-Scale Multilingual Audio Dataset
by: Samir, Farhan, et al.
Published: (2024)

AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios
by: Huang, Yuting, et al.
Published: (2025)