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StickerConv: Generating Multimodal Empathetic Responses from Scratch

Update

2024-02-16 Submission version.

2024-01-20 Ongoing work.

🍀 Overview

The overview of Agent4SC.

The architecture of PEGS framework.

⚛️ StickerConv Dataset

An example of multimodal conversation in our StickerConv dataset.

💻 Case Study

Examples of conversations by users interacting with PEGS. Users can chat with multimodal content (text and stickers) and will receive multimodal empathetic responses. Left: a conversation characterized by positive emotion (happiness). Right: a conversation characterized by negative emotion (sadness).

Related Work

SER30K: A Large-Scale Dataset for Sticker Emotion Recognition

Llava-v1: Visual Instruction Tuning

Generative Agents: Interactive Simulacra of Human Behavior

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