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07/11/2023
Attribute Controlled Dialogue Prompting
Prompt-tuning has become an increasingly popular parameter-efficient met...
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05/08/2023
LABO: Towards Learning Optimal Label Regularization via Bi-level Optimization
Regularization techniques are crucial to improving the generalization pe...
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03/24/2023
Mathematical Challenges in Deep Learning
Deep models are dominating the artificial intelligence (AI) industry sin...
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12/20/2022
KronA: Parameter Efficient Tuning with Kronecker Adapter
Fine-tuning a Pre-trained Language Model (PLM) on a specific downstream ...
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12/12/2022
Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization
Knowledge Distillation (KD) has been extensively used for natural langua...
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12/12/2022
Improving Generalization of Pre-trained Language Models via Stochastic Weight Averaging
Knowledge Distillation (KD) is a commonly used technique for improving t...
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10/14/2022
DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation
With the ever-growing size of pre-trained models (PMs), fine-tuning them...
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06/30/2022
Learning Functions on Multiple Sets using Multi-Set Transformers
We propose a general deep architecture for learning functions on multipl...
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05/25/2022
Towards Understanding Label Regularization for Fine-tuning Pre-trained Language Models
Knowledge Distillation (KD) is a prominent neural model compression tech...
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10/16/2021
Equivariant Discrete Normalizing Flows
At its core, generative modeling seeks to uncover the underlying factors...
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04/22/2020
Polarized-VAE: Proximity Based Disentangled Representation Learning for Text Generation
Learning disentangled representations of real world data is a challengin...
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03/07/2020
Generating Emotionally Aligned Responses in Dialogues using Affect Control Theory
State-of-the-art neural dialogue systems excel at syntactic and semantic...
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08/25/2019
Normalizing Flows: Introduction and Ideas
Normalizing Flows are generative models which produce tractable distribu...
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07/10/2019
Tails of Triangular Flows
Triangular maps are a construct in probability theory that allows the tr...
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05/27/2019
