Deep Cognition and Language Research (DeCLaRe) Lab
Open-source projects on GitHub: Conv Emotion, Tango and MELD
Consolidated Product Portfolio
This repository contains the official implementation code of the paper Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis, accepted at EMNLP 2021.
This repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.
This repo contains implementation of different architectures for emotion recognition in conversations.
This repository contains PyTorch implementation for the baseline models from the paper Utterance-level Dialogue Understanding: An Empirical Study
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation
JAM: A Tiny Flow-based Song Generator with Fine-grained Controllability and Aesthetic Alignment
A family of diffusion models for text-to-audio generation.
Codes and datasets of the paper Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment
This repository is maintained to release dataset and models for multimodal puzzle reasoning.
This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.
The official repo of the paper: $delta$-mem: Efficient Online Memory for Large Language Models
Company Profile & Strategy
Deep Cognition and Language Research (DeCLaRe) Lab maintains 9 open-source projects on GitHub, including Conv Emotion, Tango and MELD. Primary language: Python.
Open-Source Footprint
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