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Found 8 papers, 0 papers with code
Orca-Math: Unlocking the potential of SLMs in Grade School Math
Ensembling provides a substantial boost in accuracy but at a significant cost increase with multiple calls to the model (e. g., Phi-GSM uses top-48 to boost the performance from 68. 2 to 81. 5).
Ranked #36 on
Arithmetic Reasoning
on GSM8K
Orca 2: Teaching Small Language Models How to Reason
Research on training small LMs has often relied on imitation learning to replicate the output of more capable models.
Ranked #1 on
Crass AI
on BIG-bench
Gender-tuning: Empowering Fine-tuning for Debiasing Pre-trained Language Models
Recent studies have revealed that the widely-used Pre-trained Language Models (PLMs) propagate societal biases from the large unmoderated pre-training corpora.
Improving the Reusability of Pre-trained Language Models in Real-world Applications
The reusability of state-of-the-art Pre-trained Language Models (PLMs) is often limited by their generalization problem, where their performance drastically decreases when evaluated on examples that differ from the training dataset, known as Out-of-Distribution (OOD)/unseen examples.
Learning to Reverse DNNs from AI Programs Automatically
With the privatization deployment of DNNs on edge devices, the security of on-device DNNs has raised significant concern.
Fine-Grained Emotion Detection in Health-Related Online Posts
Detecting fine-grained emotions in online health communities provides insightful information about patients{'} emotional states.
Identifying Empathetic Messages in Online Health Communities
Empathy captures one{'}s ability to correlate with and understand others{'} emotional states and experiences.
Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network
In this study, we applied a deep LSTM structure to classify dialogue acts (DAs) in open-domain conversations.
Automatic Speech Recognition (ASR)
Dialogue Act Classification
+5
