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Found 10 papers, 1 papers with code
CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation
Alternatively, camera and radar are commonly deployed on vehicles already on the road today, but performance of Camera-Radar (CR) fusion falls behind LC fusion.
Successfully Guiding Humans with Imperfect Instructions by Highlighting Potential Errors and Suggesting Corrections
This paper addresses the challenge of leveraging imperfect language models to guide human decision-making in the context of a grounded navigation task.
LiRaFusion: Deep Adaptive LiDAR-Radar Fusion for 3D Object Detection
We propose LiRaFusion to tackle LiDAR-radar fusion for 3D object detection to fill the performance gap of existing LiDAR-radar detectors.
Hallucination Detection for Grounded Instruction Generation
We investigate the problem of generating instructions to guide humans to navigate in simulated residential environments.
Define, Evaluate, and Improve Task-Oriented Cognitive Capabilities for Instruction Generation Models
Recent work studies the cognitive capabilities of language models through psychological tests designed for humans.
Attentional Feature Refinement and Alignment Network for Aircraft Detection in SAR Imagery
Aircraft detection in Synthetic Aperture Radar (SAR) imagery is a challenging task in SAR Automatic Target Recognition (SAR ATR) areas due to aircraft's extremely discrete appearance, obvious intraclass variation, small size and serious background's interference.
The 2019 BBN Cross-lingual Information Retrieval System
In this paper, we describe a cross-lingual information retrieval (CLIR) system that, given a query in English, and a set of audio and text documents in a foreign language, can return a scored list of relevant documents, and present findings in a summary form in English.
Towards Few-Shot Event Mention Retrieval: An Evaluation Framework and A Siamese Network Approach
Previous approaches treat event extraction as {``}one size fits all{''} with an ontology defined a priori.
Cross-lingual Information Retrieval with BERT
Multiple neural language models have been developed recently, e. g., BERT and XLNet, and achieved impressive results in various NLP tasks including sentence classification, question answering and document ranking.
Weakly Supervised Attentional Model for Low Resource Ad-hoc Cross-lingual Information Retrieval
We propose a weakly supervised neural model for Ad-hoc Cross-lingual Information Retrieval (CLIR) from low-resource languages.
