Papers with psychological theory

9 papers
Predicting Responses to Psychological Questionnaires from Participants’ Social Media Posts and Question Text Embeddings (2020.findings-emnlp)

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Challenge: Existing data cannot be used to predict responses for new questions or participants.
Approach: They propose a method that uses social media texts and the text of the question to predict a participant's questionnaire response.
Outcome: The proposed method can be used to integrate new participants or new questions into psychological studies without costly data collection.
Activation-Space Personality Steering: Hybrid Layer Selection for Stable Trait Control in LLMs (2026.eacl-long)

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Challenge: Personality-aware LLMs exhibit implicit personalities in their generation, but reliably controlling or aligning these traits to meet specific needs remains an open challenge.
Approach: They propose a pipeline that extracts hidden state activations from transformer layers using the Big Five Personality Traits framework.
Outcome: The proposed model extracts hidden state activations from transformer layers using the Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness and Neuroticism)
A Survey of Large Language Models in Psychotherapy: Current Landscape and Future Directions (2025.findings-acl)

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Challenge: Large language models (LLMs) can handle extensive context and multi-turn reasoning.
Approach: They propose a taxonomy dividing psychotherapy into stages of assessment, diagnosis, and treatment to examine LLM advancements and challenges.
Outcome: The proposed taxonomy reveals imbalances in current research, such as a focus on common disorders, linguistic biases, fragmented methods, and limited theoretical integration.
PersonaForge: Psychology-Grounded Dual-Process Architecture for Personality-Consistent Role-Playing Agents (2026.findings-acl)

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Challenge: Existing approaches to role-playing with Large Language Models lack consistency across long conversations.
Approach: They propose a three-layer personality architecture grounded in psychological theory and a dual-process generation mechanism inspired by cognitive science to solve this problem.
Outcome: The proposed framework reduces drift over 50-turn conversations by reducing personality consistency . human evaluation confirms more authentic and psychologically coherent character behaviors.
“Mistakes Help Us Grow”: Facilitating and Evaluating Growth Mindset Supportive Language in Classrooms (2023.emnlp-main)

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Challenge: GMSL has been shown to significantly reduce disparities in academic achievement and enhance students’ learning outcomes.
Approach: They develop a coaching tool to reframe unsupportive utterances to GMSL using large language models.
Outcome: The proposed model outperforms the GMSL-trained teachers in fostering a growth mindset and promoting challenge-seeking behavior.
ESC-Judge: A Framework for Comparing Emotional Support Conversational Agents (2025.emnlp-main)

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Challenge: Large Language Models (LLMs) increasingly power mental-health chatbots . yet the field lacks a scalable, theory-grounded way to decide which model is more effective to deploy.
Approach: They propose a framework that grounds head-to-head comparisons of Emotional-Support LLMs in Hill’s Exploration–Insight–Action counselling model.
Outcome: The proposed framework matches PhD-level annotators in 85% of Exploration, 83% of Insight, and 86% of Action decisions, demonstrating human-level reliability at a fraction of the cost.
Can Large Language Models Identify Implicit Suicidal Ideation? An Empirical Evaluation (2025.findings-emnlp)

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Challenge: Existing data on suicidal ideation in private conversations are limited . a new dataset of 1,200 test cases is presented to address this gap .
Approach: They propose a dataset of 1,200 test cases simulating implicit suicidal ideation in private contexts.
Outcome: The proposed dataset includes 1,200 test cases simulating implicit suicidal ideation in dialogue scenarios.
PsyPath: Psychologically-guided Self-Exploration for Personality Detection (2026.findings-acl)

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Challenge: Personality detection aims to label traits via identifying linguistic cues from written text.
Approach: They propose a framework that allows large language models to generate and answer psychologically meaningful questions and a hybrid scoring mechanism to evaluate the generated nodes in the reasoning paths.
Outcome: The proposed framework outperforms baselines on two benchmark datasets and significantly improves performance and interpretability in downstream tasks.
Emotion-Wheel-Guided Audio-Referred Text Representation for Multimodal Emotion Recognition in Conversation (2026.acl-long)

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Challenge: Existing methods for Emotion Recognition in Conversation ignore their distinct communicative roles and information capacities and apply uniform penalties regardless of affective proximity.
Approach: They propose a modality-aware fusion strategy capturing linguistic features from text as the primary source and audio as a complementary component.
Outcome: The proposed method captures linguistic features from text as the primary source and audio as a complementary component and supervised contrastive loss to encode emotional proximity based on Russell’s circumplex model.

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