What do audio transformer models hear? Probing Acoustic Representations for Language Delivery and its Structure
Transformer models across multiple domains such as natural language processing and speech form an unavoidable part of the tech stack of …
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Approximate Information State for Approximate Planning and Reinforcement Learning in Partially Observed Systems
We propose a theoretical framework for approximate planning and learning in partially observed systems. Our framework is based on the …
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Automated Speech Scoring System Under The Lens: Evaluating and interpreting the linguistic cues for language proficiency
English proficiency assessments have become a necessary metric for filtering and selecting prospective candidates for both academia and …
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CoSe-Co: Text Conditioned Generative CommonSense Contextualizer
Pre-trained Language Models (PTLMs) have been shown to perform well on natural language tasks. Many prior works have leveraged …
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CyCLIP: Cyclic Contrastive Language-Image Pretraining
Recent advances in contrastive representation learning over paired image-text data have led to models such as CLIP that achieve …
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Data Instance Prior for Transfer Learning in GANs
Recent advances in generative adversarial networks (GANs) have shown remarkable progress in generating high-quality images. However, …
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LM-CORE: Language Models with Contextually Relevant External Knowledge
Large transformer-based pre-trained language models have achieved impressive performance on a variety of knowledge-intensive tasks and …
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Minimal: Mining Models for Universal Adversarial Triggers
It is well known that natural language models are vulnerable to adversarial attacks, which are mostly input-specific in nature. …
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Minimal: Mining Models for Universal Adversarial Triggers
SAC: Semantic Attention Composition for Text-Conditioned Image Retrieval
The ability to efficiently search for images is essential for improving the user experiences across various products. Incorporating …
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SARC: Soft Actor Retrospective Critic
The two-time scale nature of SAC, which is an actor-critic algorithm, is characterised by the fact that the critic estimate has not …
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