# MOCC-R1: Reinforcing Reasoning-Response Consistency for Multimodal Counselor Response Generation

arXiv: https://arxiv.org/abs/2609.17180 · HTML: https://mlsanity.com/paper/2609.17180/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 32 references that are in the map.
- First posted on arXiv 15 Sep 2026.

## Builds on (most cited first, 17 of 17)

- [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://mlsanity.com/paper/2402.03300/) (2024)
- [Towards Emotional Support Dialog Systems](https://mlsanity.com/paper/2106.01144/) (2021)
- [A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support](https://mlsanity.com/paper/2009.08441/) (2020)
- [CEM: Commonsense-aware Empathetic Response Generation](https://mlsanity.com/paper/2109.05739/) (2021)
- [MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation](https://mlsanity.com/paper/2203.13560/) (2022)
- [Cactus: Towards Psychological Counseling Conversations using Cognitive Behavioral Theory](https://mlsanity.com/paper/2407.03103/) (2024)
- [ESCoT: Towards Interpretable Emotional Support Dialogue Systems](https://mlsanity.com/paper/2406.10960/) (2024)
- [Towards Multimodal Emotional Support Conversation Systems](https://mlsanity.com/paper/2408.03650/) (2024)
- [STICKERCONV: Generating Multimodal Empathetic Responses from Scratch](https://mlsanity.com/paper/2402.01679/) (2024)
- [Towards Multimodal Empathetic Response Generation: A Rich Text-Speech-Vision Avatar-based Benchmark](https://mlsanity.com/paper/2502.04976/) (2025)
- [EmpathyEar: An Open-source Avatar Multimodal Empathetic Chatbot](https://mlsanity.com/paper/2406.15177/) (2024)
- [MIRROR: Multimodal Cognitive Reframing Therapy for Rolling with Resistance](https://mlsanity.com/paper/2504.13211/) (2025)
- [MEDIC: A Multimodal Empathy Dataset in Counseling](https://mlsanity.com/paper/2305.02842/) (2023)
- [EmpathicStories++: A Multimodal Dataset for Empathy towards Personal Experiences](https://mlsanity.com/paper/2405.15708/) (2024)
- [STRIDE-ED: A Strategy-Grounded Stepwise Reasoning Framework for Empathetic Dialogue Systems](https://mlsanity.com/paper/2604.07100/) (2026)
- [PEER: Unified Process-Outcome Reinforcement Learning for Structured Empathetic Reasoning](https://mlsanity.com/paper/2508.09521/) (2025)
- [DMT-CBT: Longitudinal Therapeutic State Modeling for CBT Counseling](https://mlsanity.com/paper/2606.03132/) (2026)

## Abstract (arXiv)

Multimodal counselor response generation (MCRG) aims to generate an appropriate counselor response from multimodal dialogue histories. Progress is limited by two gaps: first, existing datasets rarely capture sustained, human-recorded counseling interactions conducted by qualified counselors; Second, existing methods do not explicitly optimize consistency between counseling reasoning and the generated response, potentially undermining the reliability of MCRG systems. Thus, we introduce MOCC, a multimodal counseling conversation corpus containing over 200 hours of interactions involving 154 credential-verified counselors. Based on MOCC, we propose MOCC-R1, a two-stage framework for optimizing reasoning-response consistency. Cold-start supervised fine-tuning trains the model to generate a structured trajectory consisting of client-state understanding, a response intent that links a counseling principle to a planned action, and the final response. Reinforcement learning (RL) then rewards grounded plan coherence and plan execution, encouraging the inferred state and plan to be supported by the dialogue context and the response to realize that plan. Experiments demonstrate the effectiveness of the proposed MOCC-R1.