29 citations · 101 across the 19 of their papers we have counts for
21 papers
Lightweight reranking for language model generations
Siddhartha Jain, Xiaofei Ma, Anoop Deoras +1
Large Language Models (LLMs) can exhibit considerable variation in the quality of their sampled outputs. Reranking and selecting the best generation from the sampled set is a popul…
Jet substructure in neutral current deep inelastic e+p scattering at upcoming Electron-Ion Collider
Siddharth Jain, R. Aggarwal, M. Kaur
Predictions are made for the jet substructure of one-jet events produced in electron-proton neutral current deep inelastic scattering at the future Electron-Ion Collider for exchan…
Fick-Jacobs description and first passage dynamics for diffusion in a channel under stochastic resetting
Siddharth Jain, Denis Boyer, Arnab Pal +1
Transport of particles through channels is of paramount importance in physics, chemistry and surface science due to its broad real world applications. Much insights can be gained b…
RL4ReAl: Reinforcement Learning for Register Allocation
S. VenkataKeerthy, Siddharth Jain, Anilava Kundu +3
We aim to automate decades of research and experience in register allocation, leveraging machine learning. We tackle this problem by embedding a multi-agent reinforcement learning…
Further Collapses in TFNP
Mika Göös, Alexandros Hollender, Siddhartha Jain +4
We show . Here the class consists of all total search problems that reduce to the End-of-Potential-Line problem, which…
Expert Graphs: Synthesizing New Expertise via Collaboration
Bijan Mazaheri, Siddharth Jain, Jehoshua Bruck
Consider multiple experts with overlapping expertise working on a classification problem under uncertain input. What constitutes a consistent set of opinions? How can we predict th…
Robust Correction of Sampling Bias Using Cumulative Distribution Functions
Bijan Mazaheri, Siddharth Jain, Jehoshua Bruck
Varying domains and biased datasets can lead to differences between the training and the target distributions, known as covariate shift. Current approaches for alleviating this oft…
Coding for Optimized Writing Rate in DNA Storage
Siddharth Jain, Farzad Farnoud, Moshe Schwartz +1
A method for encoding information in DNA sequences is described. The method is based on the precision-resolution framework, and is aimed to work in conjunction with a recently sugg…
CodNN -- Robust Neural Networks From Coded Classification
Netanel Raviv, Siddharth Jain, Pulakesh Upadhyaya +2
Deep Neural Networks (DNNs) are a revolutionary force in the ongoing information revolution, and yet their intrinsic properties remain a mystery. In particular, it is widely known…
Overinterpretation reveals image classification model pathologies
Brandon Carter, Siddhartha Jain, Jonas Mueller +1
Image classifiers are typically scored on their test set accuracy, but high accuracy can mask a subtle type of model failure. We find that high scoring convolutional neural network…
Information Condensing Active Learning
Siddhartha Jain, Ge Liu, David Gifford
We introduce Information Condensing Active Learning (ICAL), a batch mode model agnostic Active Learning (AL) method targeted at Deep Bayesian Active Learning that focuses on acquir…
What is the Value of Data? On Mathematical Methods for Data Quality Estimation
Netanel Raviv, Siddharth Jain, Jehoshua Bruck
Data is one of the most important assets of the information age, and its societal impact is undisputed. Yet, rigorous methods of assessing the quality of data are lacking. In this…
Inapproximability of Additive Weak Contraction under SSEH and Strong UGC
Siddhartha Jain
Succinct representations of a graph have been objects of central study in computer science for decades. In this paper, we study the operation called \emph{Distance Preserving Graph…
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles
Siddhartha Jain, Ge Liu, Jonas Mueller +1
The inaccuracy of neural network models on inputs that do not stem from the training data distribution is both problematic and at times unrecognized. Model uncertainty estimation c…
What made you do this? Understanding black-box decisions with sufficient input subsets
Brandon Carter, Jonas Mueller, Siddhartha Jain +1
Local explanation frameworks aim to rationalize particular decisions made by a black-box prediction model. Existing techniques are often restricted to a specific type of predictor…
Duplication Distance to the Root for Binary Sequences
Noga Alon, Jehoshua Bruck, Farzad Farnoud +1
We study the tandem duplication distance between binary sequences and their roots. In other words, the quantity of interest is the number of tandem duplication operations of the fo…
Duplication-Correcting Codes for Data Storage in the DNA of Living Organisms
Siddharth Jain, Farzad Farnoud, Moshe Schwartz +1
The ability to store data in the DNA of a living organism has applications in a variety of areas including synthetic biology and watermarking of patented genetically-modified organ…
Capacity and Expressiveness of Genomic Tandem Duplication
Siddharth Jain, Farzad Farnoud, Jehoshua Bruck
The majority of the human genome consists of repeated sequences. An important type of repeated sequences common in the human genome are tandem repeats, where identical copies appea…
On Match Lengths, Zero Entropy and Large Deviations - with Application to Sliding Window Lempel-Ziv Algorithm
Siddharth Jain, R. K. Bansal
The Sliding Window Lempel-Ziv (SWLZ) algorithm that makes use of recurrence times and match lengths has been studied from various perspectives in information theory literature. In…
On Match Lengths and the Asymptotic Behavior of Sliding Window Lempel-Ziv Algorithm for Zero Entropy Sequences
Siddharth Jain, Rakesh Kumar Bansal
The Sliding Window Lempel-Ziv (SWLZ) algorithm has been studied from various perspectives in information theory literature. In this paper, we provide a general law which defines th…
On Large Deviation Property of Recurrence Times
Siddharth Jain, Rakesh Kumar Bansal
We extend the study by Ornstein and Weiss on the asymptotic behavior of the normalized version of recurrence times and establish the large deviation property for a certain class of…