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08/30/2023
FPTQ: Fine-grained Post-Training Quantization for Large Language Models
In the era of large-scale language models, the substantial parameter siz...
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08/21/2023
QD-BEV : Quantization-aware View-guided Distillation for Multi-view 3D Object Detection
Multi-view 3D detection based on BEV (bird-eye-view) has recently achiev...
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06/29/2023
Tokenization and the Noiseless Channel
Subword tokenization is a key part of many NLP pipelines. However, littl...
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06/29/2023
A Formal Perspective on Byte-Pair Encoding
Byte-Pair Encoding (BPE) is a popular algorithm used for tokenizing data...
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06/05/2023
Structured Voronoi Sampling
Recently, there has been a growing interest in the development of gradie...
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05/20/2023
Autoregressive Modeling with Lookahead Attention
To predict the next token, autoregressive models ordinarily examine the ...
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12/20/2022
A Measure-Theoretic Characterization of Tight Language Models
Language modeling, a central task in natural language processing, involv...
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12/16/2022
ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networks
Causal chain reasoning (CCR) is an essential ability for many decision-m...
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12/06/2022
CSQ: Growing Mixed-Precision Quantization Scheme with Bi-level Continuous Sparsification
Mixed-precision quantization has been widely applied on deep neural netw...
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11/29/2022
NoisyQuant: Noisy Bias-Enhanced Post-Training Activation Quantization for Vision Transformers
The complicated architecture and high training cost of vision transforme...
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10/18/2022
Hidden State Variability of Pretrained Language Models Can Guide Computation Reduction for Transfer Learning
While transferring a pretrained language model, common approaches conven...
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08/14/2022
Text Difficulty Study: Do machines behave the same as humans regarding text difficulty?
Given a task, human learns from easy to hard, whereas the model learns r...
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05/22/2022
A Graph Enhanced BERT Model for Event Prediction
Predicting the subsequent event for an existing event context is an impo...
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05/12/2022
e-CARE: a New Dataset for Exploring Explainable Causal Reasoning
Understanding causality has vital importance for various Natural Languag...
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02/08/2022
Binary Neural Networks as a general-propose compute paradigm for on-device computer vision
For binary neural networks (BNNs) to become the mainstream on-device com...
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10/12/2021
Memory-Efficient CNN Accelerator Based on Interlayer Feature Map Compression
Existing deep convolutional neural networks (CNNs) generate massive inte...
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09/19/2019
Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder
Understanding event and event-centered commonsense reasoning are crucial...
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09/06/2019
Training Deep Neural Networks Using Posit Number System
With the increasing size of Deep Neural Network (DNN) models, the high m...
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09/19/2017
An Analog Neural Network Computing Engine using CMOS-Compatible Charge-Trap-Transistor (CTT)
An analog neural network computing engine based on CMOS-compatible charg...
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09/19/2017
A Memristive Neural Network Computing Engine using CMOS-Compatible Charge-Trap-Transistor (CTT)
A memristive neural network computing engine based on CMOS-compatible ch...
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09/15/2017
A Streaming Accelerator for Deep Convolutional Neural Networks with Image and Feature Decomposition for Resource-limited System Applications
Deep convolutional neural networks (CNN) are widely used in modern artif...
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07/08/2017
A Reconfigurable Streaming Deep Convolutional Neural Network Accelerator for Internet of Things
Convolutional neural network (CNN) offers significant accuracy in image ...
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03/05/2017
A/D Converter Architectures for Energy-Efficient Vision Processor
AI applications have emerged in current world. Among AI applications, co...
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01/31/2017
1.5 bit-per-stage 8-bit Pipelined CMOS A/D Converter for Neuromophic Vision Processor
Neuromorphic vision processor is an electronic implementation of vision ...
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12/25/2016