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Found 14 papers, 8 papers with code
Unsupervised Dialogue Topic Segmentation in Hyperdimensional Space
We open-source HyperSeg to provide a strong baseline for unsupervised topic segmentation.
Toward a Better Understanding of Loss Functions for Collaborative Filtering
Inspired by this analysis, we propose a novel loss function that improves the design of alignment and uniformity considering the unique patterns of datasets called Margin-aware Alignment and Weighted Uniformity (MAWU).
uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative Filtering
In this paper, we propose Unbiased ConTrastive Representation Learning (uCTRL), optimizing alignment and uniformity functions derived from the InfoNCE loss function for CF models.
SPADE: Sparse Pillar-based 3D Object Detection Accelerator for Autonomous Driving
3D object detection using point cloud (PC) data is essential for perception pipelines of autonomous driving, where efficient encoding is key to meeting stringent resource and latency requirements.
Teacher Intervention: Improving Convergence of Quantization Aware Training for Ultra-Low Precision Transformers
Pre-trained Transformer models such as BERT have shown great success in a wide range of applications, but at the cost of substantial increases in model complexity.
Automatic Network Adaptation for Ultra-Low Uniform-Precision Quantization
Uniform-precision neural network quantization has gained popularity since it simplifies densely packed arithmetic unit for high computing capability.
Leveraging Non-dialogue Summaries for Dialogue Summarization
To mitigate the lack of diverse dialogue summarization datasets in academia, we present methods to utilize non-dialogue summarization data for enhancing dialogue summarization systems.
LIME: Weakly-Supervised Text Classification Without Seeds
With just an off-the-shelf textual entailment model, LIME outperforms recent baselines in weakly-supervised text classification and achieves state-of-the-art in 4 benchmarks.
Bilateral Self-unbiased Learning from Biased Implicit Feedback
Implicit feedback has been widely used to build commercial recommender systems.
Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion
We advance the state-of-the-art in unsupervised abstractive dialogue summarization by utilizing multi-sentence compression graphs.
NN-LUT: Neural Approximation of Non-Linear Operations for Efficient Transformer Inference
Non-linear operations such as GELU, Layer normalization, and Softmax are essential yet costly building blocks of Transformer models.
Finetuning Pretrained Transformers into Variational Autoencoders
Text variational autoencoders (VAEs) are notorious for posterior collapse, a phenomenon where the model's decoder learns to ignore signals from the encoder.
Improving Distinction between ASR Errors and Speech Disfluencies with Feature Space Interpolation
Fine-tuning pretrained language models (LMs) is a popular approach to automatic speech recognition (ASR) error detection during post-processing.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Uniform-Precision Neural Network Quantization via Neural Channel Expansion
Uniform-precision neural network quantization has gained popularity thanks to its simple arithmetic unit densely packed for high computing capability.
