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Found 13 papers, 6 papers with code
DiffuCOMET: Contextual Commonsense Knowledge Diffusion
Inferring contextually-relevant and diverse commonsense to understand narratives remains challenging for knowledge models.
A Robust Super-resolution Gridless Imaging Framework for UAV-borne SAR Tomography
This paper presents an innovative gridless 3-D imaging framework tailored for UAV-borne TomoSAR.
Efficient Tool Use with Chain-of-Abstraction Reasoning
LLM agents trained with our method also show more efficient tool use, with inference speed being on average ~1. 4x faster than baseline tool-augmented LLMs.
PeaCoK: Persona Commonsense Knowledge for Consistent and Engaging Narratives
They must also learn to maintain consistent speaker personas for themselves throughout the narrative, so that their counterparts feel involved in a realistic conversation or story.
Efficient Gridless DoA Estimation Method of Non-uniform Linear Arrays with Applications in Automotive Radars
This paper focuses on the gridless direction-of-arrival (DoA) estimation for data acquired by non-uniform linear arrays (NLAs) in automotive applications.
ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold
In addition, adaptive threshold is introduced for each azimuth-range pixel, enabling the threshold shrinkage to be not only layer-varied but also element-wise.
ComFact: A Benchmark for Linking Contextual Commonsense Knowledge
Understanding rich narratives, such as dialogues and stories, often requires natural language processing systems to access relevant knowledge from commonsense knowledge graphs.
TomoSAR-ALISTA: Efficient TomoSAR Imaging via Deep Unfolded Network
Synthetic aperture radar (SAR) tomography (TomoSAR) has attracted remarkable interest for its ability in achieving three-dimensional reconstruction along the elevation direction from multiple observations.
Gridless Tomographic SAR Imaging Based on Accelerated Atomic Norm Minimization with Efficiency
The resolving along the elevation direction can be treated as a line spectrum estimation problem.
End-to-End Task-Oriented Dialog Modeling with Semi-Structured Knowledge Management
To address this task, we propose a TOD system with semi-structured knowledge management, SeKnow, which extends the belief state to manage knowledge with both structured and unstructured contents.
HyKnow: End-to-End Task-Oriented Dialog Modeling with Hybrid Knowledge Management
To address this task, we propose a TOD system with hybrid knowledge management, HyKnow.
Paraphrase Augmented Task-Oriented Dialog Generation
Neural generative models have achieved promising performance on dialog generation tasks if given a huge data set.
Integrating Discrete and Neural Features via Mixed-feature Trans-dimensional Random Field Language Models
There has been a long recognition that discrete features (n-gram features) and neural network based features have complementary strengths for language models (LMs).
