Cover Image

Towards Privacy-aware Mental Health AI Models: Advances, Challenges, and Opportunities

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mandal, Aishik, Chakraborty, Tanmoy, Gurevych, Iryna
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MAGneT: Coordinated Multi-Agent Generation of Synthetic Multi-Turn Mental Health Counseling Sessions
by: Mandal, Aishik, et al.
Published: (2025)

A Comprehensive Review of Datasets for Clinical Mental Health AI Systems
by: Mandal, Aishik, et al.
Published: (2025)

SciCoQA: Quality Assurance for Scientific Paper--Code Alignment
by: Baumgärtner, Tim, et al.
Published: (2026)

Towards Automated Error Discovery: A Study in Conversational AI
by: Petrak, Dominic, et al.
Published: (2025)

IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators
by: Paul, Indraneil, et al.
Published: (2024)

Preemptive Detection and Correction of Misaligned Actions in LLM Agents
by: Fang, Haishuo, et al.
Published: (2024)

Factual Self-Awareness in Language Models: Representation, Robustness, and Scaling
by: Tamoyan, Hovhannes, et al.
Published: (2025)

Multimodal Large Language Models to Support Real-World Fact-Checking
by: Geng, Jiahui, et al.
Published: (2024)

Enhancing Depression Detection via Question-wise Modality Fusion
by: Mandal, Aishik, et al.
Published: (2025)

Can LLMs Automate Fact-Checking Article Writing?
by: Sahnan, Dhruv, et al.
Published: (2025)

Graph2Counsel: Clinically Grounded Synthetic Counseling Dialogue Generation from Client Psychological Graphs
by: Mandal, Aishik, et al.
Published: (2026)

Sensitivity, Performance, Robustness: Deconstructing the Effect of Sociodemographic Prompting
by: Beck, Tilman, et al.
Published: (2023)

PeerQA: A Scientific Question Answering Dataset from Peer Reviews
by: Baumgärtner, Tim, et al.
Published: (2025)

Co-FactChecker: A Framework for Human-AI Collaborative Claim Verification Using Large Reasoning Models
by: Sahnan, Dhruv, et al.
Published: (2026)

SPARE: Single-Pass Annotation with Reference-Guided Evaluation for Automatic Process Supervision and Reward Modelling
by: Rizvi, Md Imbesat Hassan, et al.
Published: (2025)

SpaRC and SpaRP: Spatial Reasoning Characterization and Path Generation for Understanding Spatial Reasoning Capability of Large Language Models
by: Rizvi, Md Imbesat Hassan, et al.
Published: (2024)

Mechanistic Behavior Editing of Language Models
by: Singh, Joykirat, et al.
Published: (2024)

The Good, the Bad and the Constructive: Automatically Measuring Peer Review's Utility for Authors
by: Sadallah, Abdelrahman, et al.
Published: (2025)

HIDE and Seek: Detecting Hallucinations in Language Models via Decoupled Representations
by: Chatterjee, Anwoy, et al.
Published: (2025)

$\texttt{LM}^\texttt{2}$: A Simple Society of Language Models Solves Complex Reasoning
by: Juneja, Gurusha, et al.
Published: (2024)

A Survey of Confidence Estimation and Calibration in Large Language Models
by: Geng, Jiahui, et al.
Published: (2023)

DOCE: Finding the Sweet Spot for Execution-Based Code Generation
by: Li, Haau-Sing, et al.
Published: (2024)

Hypothesis-Driven Feature Manifold Analysis in LLMs via Supervised Multi-Dimensional Scaling
by: Tiblias, Federico, et al.
Published: (2025)

From Leaky Thoughts to Private Reasoning: Controlling What LRMs Say to Themselves
by: Puerto, Haritz, et al.
Published: (2026)

Uncertainty-Aware Decoding with Minimum Bayes Risk
by: Daheim, Nico, et al.
Published: (2025)

CORE-T: COherent REtrieval of Tables for Text-to-SQL
by: Soliman, Hassan, et al.
Published: (2026)

Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors
by: Daheim, Nico, et al.
Published: (2024)

Illusion or Algorithm? Investigating Memorization, Emergence, and Symbolic Processing in In-Context Learning
by: Niu, Jingcheng, et al.
Published: (2025)

From Chaos to Clarity: Claim Normalization to Empower Fact-Checking
by: Sundriyal, Megha, et al.
Published: (2023)

Model Merging by Uncertainty-Based Gradient Matching
by: Daheim, Nico, et al.
Published: (2023)

Self-Evolved Preference Optimization for Enhancing Mathematical Reasoning in Small Language Models
by: Singh, Joykirat, et al.
Published: (2025)

A Framework for Situating Innovations, Opportunities, and Challenges in Advancing Vertical Systems with Large AI Models
by: Verma, Gaurav, et al.
Published: (2025)

Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoning
by: Juneja, Gurusha, et al.
Published: (2023)

From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning
by: Dinucu-Jianu, David, et al.
Published: (2025)

ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding
by: Paul, Indraneil, et al.
Published: (2025)

Dialogue Agents 101: A Beginner's Guide to Critical Ingredients for Designing Effective Conversational Systems
by: Kumar, Shivani, et al.
Published: (2023)

Can LLMs replace Neil deGrasse Tyson? Evaluating the Reliability of LLMs as Science Communicators
by: Bajpai, Prasoon, et al.
Published: (2024)

Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health
by: Tian, Shubo, et al.
Published: (2023)

CSEval: Towards Automated, Multi-Dimensional, and Reference-Free Counterspeech Evaluation using Auto-Calibrated LLMs
by: Hengle, Amey, et al.
Published: (2025)

SemEval 2024 -- Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)
by: Kumar, Shivani, et al.
Published: (2024)