3 citations · 4 across the 6 of their papers we have counts for
9 papers
An Information-Theoretic Perspective on LLM Tokenizers
Mete Erdogan, Abhiram Gorle, Shubham Chandak +2
Large language model (LLM) tokenizers act as structured compressors: by mapping text to discrete token sequences, they determine token count (and thus compute and context usage) an…
Txt2Vid: Ultra-Low Bitrate Compression of Talking-Head Videos via Text
Pulkit Tandon, Shubham Chandak, Pat Pataranutaporn +5
Video represents the majority of internet traffic today, driving a continual race between the generation of higher quality content, transmission of larger file sizes, and the devel…
On Coding for an Abstracted Nanopore Channel for DNA Storage
Reyna Hulett, Shubham Chandak, Mary Wootters
In the emerging field of DNA storage, data is encoded as DNA sequences and stored. The data is read out again by sequencing the stored DNA. Nanopore sequencing is a new sequencing…
Reducing latency and bandwidth for video streaming using keypoint extraction and digital puppetry
Roshan Prabhakar, Shubham Chandak, Carina Chiu +4
COVID-19 has made video communication one of the most important modes of information exchange. While extensive research has been conducted on the optimization of the video streamin…
DZip: improved general-purpose lossless compression based on novel neural network modeling
Mohit Goyal, Kedar Tatwawadi, Shubham Chandak +1
We consider lossless compression based on statistical data modeling followed by prediction-based encoding, where an accurate statistical model for the input data leads to substanti…
LFZip: Lossy compression of multivariate floating-point time series data via improved prediction
Shubham Chandak, Kedar Tatwawadi, Chengtao Wen +3
Time series data compression is emerging as an important problem with the growth in IoT devices and sensors. Due to the presence of noise in these datasets, lossy compression can o…
Tutorial on algebraic deletion correction codes
Kedar Tatwawadi, Shubham Chandak
The deletion channel is known to be a notoriously diffcult channel to design error-correction codes for. In spite of this difficulty, there are some beautiful code constructions wh…
DeepZip: Lossless Data Compression using Recurrent Neural Networks
Mohit Goyal, Kedar Tatwawadi, Shubham Chandak +1
Sequential data is being generated at an unprecedented pace in various forms, including text and genomic data. This creates the need for efficient compression mechanisms to enable…
Towards improved lossy image compression: Human image reconstruction with public-domain images
Ashutosh Bhown, Soham Mukherjee, Sean Yang +5
Lossy image compression has been studied extensively in the context of typical loss functions such as RMSE, MS-SSIM, etc. However, compression at low bitrates generally produces un…