Sameer Dharur
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View article: Device-Directed Speech Detection for Follow-up Conversations Using Large Language Models
Device-Directed Speech Detection for Follow-up Conversations Using Large Language Models Open
Follow-up conversations with virtual assistants (VAs) enable a user to seamlessly interact with a VA without the need to repeatedly invoke it using a keyword (after the first query). Therefore, accurate Device-directed Speech Detection (DD…
View article: Multimodal Large Language Models with Fusion Low Rank Adaptation for Device Directed Speech Detection
Multimodal Large Language Models with Fusion Low Rank Adaptation for Device Directed Speech Detection Open
Although Large Language Models (LLMs) have shown promise for human-like conversations, they are primarily pre-trained on text data. Incorporating audio or video improves performance, but collecting large-scale multimodal data and pre-train…
View article: Modality Dropout for Multimodal Device Directed Speech Detection using Verbal and Non-Verbal Features
Modality Dropout for Multimodal Device Directed Speech Detection using Verbal and Non-Verbal Features Open
Device-directed speech detection (DDSD) is the binary classification task of distinguishing between queries directed at a voice assistant versus side conversation or background speech. State-of-the-art DDSD systems use verbal cues, e.g aco…
View article: Episodic Memory Question Answering
Episodic Memory Question Answering Open
Egocentric augmented reality devices such as wearable glasses passively capture visual data as a human wearer tours a home environment. We envision a scenario wherein the human communicates with an AI agent powering such a device by asking…
View article: Habitat 2.0: Training Home Assistants to Rearrange their Habitat
Habitat 2.0: Training Home Assistants to Rearrange their Habitat Open
We introduce Habitat 2.0 (H2.0), a simulation platform for training virtual robots in interactive 3D environments and complex physics-enabled scenarios. We make comprehensive contributions to all levels of the embodied AI stack - data, sim…
View article: SOrT-ing VQA Models : Contrastive Gradient Learning for Improved Consistency
SOrT-ing VQA Models : Contrastive Gradient Learning for Improved Consistency Open
Recent research in Visual Question Answering (VQA) has revealed state-of-the-art models to be inconsistent in their understanding of the world -- they answer seemingly difficult questions requiring reasoning correctly but get simpler assoc…
View article: asensio-lab/transformer-EV-topic-classification: Transformer-EV-topic-classification-v1
asensio-lab/transformer-EV-topic-classification: Transformer-EV-topic-classification-v1 Open
Transformer Algorithm EV topic classification version 1
View article: Extracting User Behavior at Electric Vehicle Charging Stations with Transformer Deep Learning Models
Extracting User Behavior at Electric Vehicle Charging Stations with Transformer Deep Learning Models Open
Mobile applications have become widely popular for their ability to access real-time information. In electric vehicle (EV) mobility, these applications are used by drivers to locate charging stations in public spaces, pay for charging tran…
View article: EV Transformer Deep Learning Topic Classification Model Weights
EV Transformer Deep Learning Topic Classification Model Weights Open
Data includes deep learning weights for transformer neural network models, trained with EV charging station user reviews with human expert annotators to conduct multilabel topic classification. These weights accompany the paper titled "Top…