mlsanityData to 14 Oct 2026

psytechlab at CLPsych 2026: Utilising Natural Language Processing methods and Large Language Models for Social Media Text Analysis

arXiv 2607.03003 ↗First posted 3 Jul 2026cs.CLcited by 0

Not on the map. Why?

Abstract (arXiv)

Social media posts are a rich and valuable source of data for analyzing mental health states and users' well-being using automated analysis tools. In this work, we demonstrate how we used a range of Natural Language Processing (NLP) methods, including Long Short-Term Memory (LSTM), BERT-based models, and Large Language Models (LLMs), for self-state and well-being analysis and summarization during the CLPsych Shared Task 2026. Our approach achieved one of the top Consistency and Contradiction scores for the summarization task and also middle-level results for the other tasks. By testing and developing such mental health-state estimation systems, we contributed to improving mental health support systems. We make our code available https://github.com/psytechlab/CLPsych2026/.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 24 references that are in the map. First posted on arXiv 3 Jul 2026.

Builds on

9 of 24 references.

References · 9

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2024The Llama 3 Herd of Modelscited by 14,715
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  4. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  5. 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,501
  6. 2024Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inferencecited by 554
  7. 2016Neural Architectures for Named Entity Recognitioncited by 550
  8. 2020TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classificationcited by 417
  9. 2024TempoFormer: A Transformer for Temporally-aware Representations in Change Detectioncited by 5

Built on by

Not cited yet.