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Found 15 papers, 8 papers with code
Adversities are all you need: Classification of self-reported breast cancer posts on Twitter using Adversarial Fine-tuning
In this paper, we describe our system entry for Shared Task 8 at SMM4H-2021, which is on automatic classification of self-reported breast cancer posts on Twitter.
From Words to Music: A Study of Subword Tokenization Techniques in Symbolic Music Generation
Subword tokenization has been widely successful in text-based natural language processing (NLP) tasks with Transformer-based models.
GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformers
We trained a BERT model for downstream genre classification and used it to assess the results obtained with the genre-CTRL model.
CounterGeDi: A controllable approach to generate polite, detoxified and emotional counterspeech
We generate counterspeech using three datasets and observe significant improvement across different attribute scores.
Doing More by Doing Less: How Structured Partial Backpropagation Improves Deep Learning Clusters
This simultaneously reduces network bandwidth, compute utilization, and memory footprint while preserving model quality.
DadaGP: A Dataset of Tokenized GuitarPro Songs for Sequence Models
In this work, we present DadaGP, a new symbolic music dataset comprising 26, 181 song scores in the GuitarPro format covering 739 musical genres, along with an accompanying tokenized format well-suited for generative sequence models such as the Transformer.
Quantum Artificial Intelligence for the Science of Climate Change
Climate change has become one of the biggest global problems increasingly compromising the Earth's habitability.
Team Phoenix at WASSA 2021: Emotion Analysis on News Stories with Pre-Trained Language Models
We describe our system entry for the WASSA 2021 Shared Task (for both Track-1 and Track-2), where we leveraged the information from Pre-trained language models for Track-specific Tasks.
Accelerating Deep Learning Inference via Learned Caches
We present the design of GATI, an end-to-end prediction serving system that incorporates learned caches for low-latency DNN inference.
Hostility Detection in Hindi leveraging Pre-Trained Language Models
This paper harnesses attention based pre-trained models fine-tuned on Hindi data with Hostile-Non hostile task as Auxiliary and fusing its features for further sub-tasks classification.
Can Adversarial Weight Perturbations Inject Neural Backdoors?
We introduce adversarial perturbations in the model weights using a composite loss on the predictions of the original model and the desired trigger through projected gradient descent.
MA-DST: Multi-Attention Based Scalable Dialog State Tracking
Task oriented dialog agents provide a natural language interface for users to complete their goal.
Translating Web Search Queries into Natural Language Questions
For example, for the user entered query "capital of USA", the most probable question intent is "What's the capital of USA?".
Accelerating Deep Learning Inference via Freezing
In this work, we observe that caching intermediate layer outputs can help us avoid running all the layers of a DNN for a sizeable fraction of inference requests.
MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines
To fix the noisy state annotations, we use crowdsourced workers to re-annotate state and utterances based on the original utterances in the dataset.
Ranked #16 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.0
Dialogue State Tracking
Multi-domain Dialogue State Tracking
