arXiv subjects

Deepak Kumar

Publications and source records attributed to Deepak Kumar.

At least 91 records · Page 5Linked to original sources

arXiv2024

Specious Sites: Tracking the Spread and Sway of Spurious News Stories at Scale

Misinformation, propaganda, and outright lies proliferate on the web, with some narratives having dangerous real-world consequences on public health, elections, and individual safety. However, despite the impact of misinformation, the research community largely lacks automated and programmatic approaches for tracking news narratives across online platforms. In this work, utilizing daily scrapes of 1,334 unreliable news websites, the large-language model MPNet, and DP-Means clustering, we introduce a system to automatically identify and track the narratives spread within online ecosystems. Identifying 52,036 narratives on these 1,334 websites, we describe the most prevalent narratives spread in 2022 and identify the most influential websites that originate and amplify narratives. Finally, we show how our system can be utilized to detect new narratives originating from unreliable news websites and to aid fact-checkers in more quickly addressing misinformation. We release code and data at https://github.com/hanshanley/specious-sites.

cs.SI↗

arXiv2024

Discrete symmetries tested at 10$^{-4}$ precision using linear polarization of photons from positronium annihilations

Discrete symmetries play an important role in particle physics with violation of CP connected to the matter-antimatter imbalance in the Universe. We report the most precise test of P, T and CP invariance in decays of ortho-positronium, performed with methodology involving polarization of photons from these decays. Positronium, the simplest bound state of an electron and positron, is of recent interest with discrepancies reported between measured hyperfine energy structure and theory at the level of $10^{-4}$ signaling a need for better understanding of the positronium system at this level. We test discrete symmetries using photon polarizations determined via Compton scattering in the dedicated J-PET tomograph on an event-by-event basis and without the need to control the spin of the positronium with an external magnetic field, in contrast to previous experiments. Our result is consistent with QED expectations at the level of 0.0007 and one standard deviation.

hep-ph↗

arXiv2024

Watch Your Language: Investigating Content Moderation with Large Language Models

Large language models (LLMs) have exploded in popularity due to their ability to perform a wide array of natural language tasks. Text-based content moderation is one LLM use case that has received recent enthusiasm, however, there is little research investigating how LLMs perform in content moderation settings. In this work, we evaluate a suite of commodity LLMs on two common content moderation tasks: rule-based community moderation and toxic content detection. For rule-based community moderation, we instantiate 95 subcommunity specific LLMs by prompting GPT-3.5 with rules from 95 Reddit subcommunities. We find that GPT-3.5 is effective at rule-based moderation for many communities, achieving a median accuracy of 64% and a median precision of 83%. For toxicity detection, we evaluate a suite of commodity LLMs (GPT-3, GPT-3.5, GPT-4, Gemini Pro, LLAMA 2) and show that LLMs significantly outperform currently widespread toxicity classifiers. However, recent increases in model size add only marginal benefit to toxicity detection, suggesting a potential performance plateau for LLMs on toxicity detection tasks. We conclude by outlining avenues for future work in studying LLMs and content moderation.

cs.HC↗

arXiv2023

Do Users Write More Insecure Code with AI Assistants?

We conduct the first large-scale user study examining how users interact with an AI Code assistant to solve a variety of security related tasks across different programming languages. Overall, we find that participants who had access to an AI assistant based on OpenAI's codex-davinci-002 model wrote significantly less secure code than those without access. Additionally, participants with access to an AI assistant were more likely to believe they wrote secure code than those without access to the AI assistant. Furthermore, we find that participants who trusted the AI less and engaged more with the language and format of their prompts (e.g. re-phrasing, adjusting temperature) provided code with fewer security vulnerabilities. Finally, in order to better inform the design of future AI-based Code assistants, we provide an in-depth analysis of participants' language and interaction behavior, as well as release our user interface as an instrument to conduct similar studies in the future.

cs.CR↗

arXiv2023

A Golden Age: Conspiracy Theories' Relationship with Misinformation Outlets, News Media, and the Wider Internet

Do we live in a "Golden Age of Conspiracy Theories?" In the last few decades, conspiracy theories have proliferated on the Internet with some having dangerous real-world consequences. A large contingent of those who participated in the January 6th attack on the US Capitol fervently believed in the QAnon conspiracy theory. In this work, we study the relationships amongst five prominent conspiracy theories (QAnon, COVID, UFO/Aliens, 9/11, and Flat-Earth) and each of their respective relationships to the news media, both authentic news and misinformation. Identifying and publishing a set of 755 different conspiracy theory websites dedicated to our five conspiracy theories, we find that each set often hyperlinks to the same external domains, with COVID and QAnon conspiracy theory websites having the largest amount of shared connections. Examining the role of news media, we further find that not only do outlets known for spreading misinformation hyperlink to our set of conspiracy theory websites more often than authentic news websites but also that this hyperlinking increased dramatically between 2018 and 2021, with the advent of QAnon and the start of COVID-19 pandemic. Using partial Granger-causality, we uncover several positive correlative relationships between the hyperlinks from misinformation websites and the popularity of conspiracy theory websites, suggesting the prominent role that misinformation news outlets play in popularizing many conspiracy theories.

cs.CY↗

arXiv2023

GroundLink: A Dataset Unifying Human Body Movement and Ground Reaction Dynamics

The physical plausibility of human motions is vital to various applications in fields including but not limited to graphics, animation, robotics, vision, biomechanics, and sports science. While fully simulating human motions with physics is an extreme challenge, we hypothesize that we can treat this complexity as a black box in a data-driven manner if we focus on the ground contact, and have sufficient observations of physics and human activities in the real world. To prove our hypothesis, we present GroundLink, a unified dataset comprised of captured ground reaction force (GRF) and center of pressure (CoP) synchronized to standard kinematic motion captures. GRF and CoP of GroundLink are not simulated but captured at high temporal resolution using force platforms embedded in the ground for uncompromising measurement accuracy. This dataset contains 368 processed motion trials (~1.59M recorded frames) with 19 different movements including locomotion and weight-shifting actions such as tennis swings to signify the importance of capturing physics paired with kinematics. GroundLinkNet, our benchmark neural network model trained with GroundLink, supports our hypothesis by predicting GRFs and CoPs accurately and plausibly on unseen motions from various sources. The dataset, code, and benchmark models are made public for further research on various downstream tasks leveraging the rich physics information at https://csr.bu.edu/groundlink/.

cs.GR↗

arXiv2023

The role of molecular structure on the microscopic thermodynamics: unveiling with Femtosecond Optical Tweezers

Microscopic thermodynamic studies can elucidate specific molecular interactions. In this work, we report the microscopic thermodynamics in binary liquid mixtures, which elucidate the role of molecular structure in nonlinear solvent response using femtosecond optical tweezers (FOT). We obtain the excess thermodynamics property of mixing in various Newtonian liquid mixtures by analyzing Microrheology data from FOT. Using our noninvasive 780 nm pulse laser we have trapped micron-sized particles to show how excess viscosity and residual Gibbs free energy change due to mixing. Furthermore, we establish from this study that hydrocarbon chain length and branching can modulate microscopic thermodynamics through intermolecular interaction. This work sheds light on the relationship between thermodynamic properties and viscosity, which is of immense importance for predicting transport properties, mixing, and chemical reactions.

physics.chem-ph↗

arXiv2023

Parameter-efficient Modularised Bias Mitigation via AdapterFusion

Large pre-trained language models contain societal biases and carry along these biases to downstream tasks. Current in-processing bias mitigation approaches (like adversarial training) impose debiasing by updating a model's parameters, effectively transferring the model to a new, irreversible debiased state. In this work, we propose a novel approach to develop stand-alone debiasing functionalities separate from the model, which can be integrated into the model on-demand, while keeping the core model untouched. Drawing from the concept of AdapterFusion in multi-task learning, we introduce DAM (Debiasing with Adapter Modules) - a debiasing approach to first encapsulate arbitrary bias mitigation functionalities into separate adapters, and then add them to the model on-demand in order to deliver fairness qualities. We conduct a large set of experiments on three classification tasks with gender, race, and age as protected attributes. Our results show that DAM improves or maintains the effectiveness of bias mitigation, avoids catastrophic forgetting in a multi-attribute scenario, and maintains on-par task performance, while granting parameter-efficiency and easy switching between the original and debiased models.

cs.CL↗

arXiv2023

Robust universal relations in neutron star asteroseismology

The non-radial oscillations of the neutron stars (NSs) have been suggested as a useful tool to probe the composition of neutron star matter (NSM). With this scope in mind, we consider a large number of equations of states (EOSs) that are consistent with nuclear matter properties and pure neutron matter EOS based on a chiral effective field theory (chEFT) calculation for the low densities and perturbative QCD EOS at very high densities. This ensemble of EOSs is also consistent with astronomical observations, gravitational waves in GW170817, mass and radius measurements from Neutron star Interior Composition ExploreR (NICER). We analyze the robustness of known universal relations (URs) among the quadrupolar $f$ mode frequencies, masses and radii with such a large number of EOSs and we find a new UR that results from a strong correlation between the $f$ mode frequencies and the radii of NSs. Such a correlation is very useful in accurately determining the radius from a measurement of $f$ mode frequencies in the near future. We also show that the quadrupolar $f$ mode frequencies of NS of masses 2.0 M$_\odot$ and above lie in the range $\sim$ 2-3 kHz in this ensemble of physically realistic EOSs. A NS of mass 2M$_{\odot}$ with a low $f$ mode frequency may indicate the existence of non-nucleonic degrees of freedom.

nucl-th↗

arXiv2023

Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks

Societal biases are reflected in large pre-trained language models and their fine-tuned versions on downstream tasks. Common in-processing bias mitigation approaches, such as adversarial training and mutual information removal, introduce additional optimization criteria, and update the model to reach a new debiased state. However, in practice, end-users and practitioners might prefer to switch back to the original model, or apply debiasing only on a specific subset of protected attributes. To enable this, we propose a novel modular bias mitigation approach, consisting of stand-alone highly sparse debiasing subnetworks, where each debiasing module can be integrated into the core model on-demand at inference time. Our approach draws from the concept of \emph{diff} pruning, and proposes a novel training regime adaptable to various representation disentanglement optimizations. We conduct experiments on three classification tasks with gender, race, and age as protected attributes. The results show that our modular approach, while maintaining task performance, improves (or at least remains on-par with) the effectiveness of bias mitigation in comparison with baseline finetuning. Particularly on a two-attribute dataset, our approach with separately learned debiasing subnetworks shows effective utilization of either or both the subnetworks for selective bias mitigation.

cs.LG↗

arXiv2023

"A Special Operation": A Quantitative Approach to Dissecting and Comparing Different Media Ecosystems' Coverage of the Russo-Ukrainian War

The coverage of the Russian invasion of Ukraine has varied widely between Western, Russian, and Chinese media ecosystems with propaganda, disinformation, and narrative spins present in all three. By utilizing the normalized pointwise mutual information metric, differential sentiment analysis, word2vec models, and partially labeled Dirichlet allocation, we present a quantitative analysis of the differences in coverage amongst these three news ecosystems. We find that while the Western press outlets have focused on the military and humanitarian aspects of the war, Russian media have focused on the purported justifications for the "special military operation" such as the presence in Ukraine of "bio-weapons" and "neo-nazis", and Chinese news media have concentrated on the conflict's diplomatic and economic consequences. Detecting the presence of several Russian disinformation narratives in the articles of several Chinese outlets, we finally measure the degree to which Russian media has influenced Chinese coverage across Chinese outlets' news articles, Weibo accounts, and Twitter accounts. Our analysis indicates that since the Russian invasion of Ukraine, Chinese state media outlets have increasingly cited Russian outlets as news sources and spread Russian disinformation narratives.

cs.CY↗

arXiv2023

Happenstance: Utilizing Semantic Search to Track Russian State Media Narratives about the Russo-Ukrainian War On Reddit

In the buildup to and in the weeks following the Russian Federation's invasion of Ukraine, Russian state media outlets output torrents of misleading and outright false information. In this work, we study this coordinated information campaign in order to understand the most prominent state media narratives touted by the Russian government to English-speaking audiences. To do this, we first perform sentence-level topic analysis using the large-language model MPNet on articles published by ten different pro-Russian propaganda websites including the new Russian "fact-checking" website waronfakes.com. Within this ecosystem, we show that smaller websites like katehon.com were highly effective at publishing topics that were later echoed by other Russian sites. After analyzing this set of Russian information narratives, we then analyze their correspondence with narratives and topics of discussion on the r/Russia and 10 other political subreddits. Using MPNet and a semantic search algorithm, we map these subreddits' comments to the set of topics extracted from our set of Russian websites, finding that 39.6% of r/Russia comments corresponded to narratives from pro-Russian propaganda websites compared to 8.86% on r/politics.

cs.SI↗

arXiv2023

CERTainty: Detecting DNS Manipulation at Scale using TLS Certificates

DNS manipulation is an increasingly common technique used by censors and other network adversaries to prevent users from accessing restricted Internet resources and hijack their connections. Prior work in detecting DNS manipulation relies largely on comparing DNS resolutions with trusted control results to identify inconsistencies. However, the emergence of CDNs and other cloud providers practicing content localization and load balancing leads to these heuristics being inaccurate, paving the need for more verifiable signals of DNS manipulation. In this paper, we develop a new technique, CERTainty, that utilizes the widely established TLS certificate ecosystem to accurately detect DNS manipulation, and obtain more information about the adversaries performing such manipulation. We find that untrusted certificates, mismatching hostnames, and blockpages are powerful proxies for detecting DNS manipulation. Our results show that previous work using consistency-based heuristics is inaccurate, allowing for 72.45% false positives in the cases detected as DNS manipulation. Further, we identify 17 commercial DNS filtering products in 52 countries, including products such as SafeDNS, SkyDNS, and Fortinet, and identify the presence of 55 ASes in 26 countries that perform ISP-level DNS manipulation. We also identify 226 new blockpage clusters that are not covered by previous research. We are integrating techniques used by CERTainty into active measurement platforms to continuously and accurately monitor DNS manipulation.

cs.CR↗

arXiv2023

Comparative studies of the sensitivities of sparse and full geometries of Total-Body PET scanners built from crystals and plastic scintillators

Background: Total-Body imaging offers high sensitivity, single-bed position, and low dose, but high construction costs limit worldwide utilization. This study compares existing and developing tomographs using plastic scintillators via simulations to propose a cost-efficient Total-Body PET scanner. Methods: Simulations of eight uEXPLORER tomographs with different scintillator materials, axial field-of-view, and detector configuration, and eight J-PET scanners with various field-of-view, plastic scintillator cross-sections, and layers were performed. Biograph Vision was also simulated. Two types of simulations were conducted with a central source and a water-filled phantom. Results: BGO crystal-based scanners showed the best sensitivity (350 cps/kBq at the center). Sparse geometry or LYSO crystals reduced sensitivity. J-PET design showed similar sensitivity to sparse LYSO detectors, with full body coverage and additional gain for brain imaging. Conclusion: The J-PET tomography system using plastic scintillators could be a cost-efficient alternative for Total-Body PET scanners, overcoming high construction costs while maintaining sensitivity

physics.med-ph↗

arXiv2023

Dynamic Optimization for Monoclonal Antibody Production

This paper presents a dynamic optimization numerical case study for Monoclonal Antibody (mAb) production. The fermentation is conducted in a continuous perfusion reactor. We represent the existing model in terms of a general modeling methodology well-suited for simulation and optimization. The model consists of six ordinary differential equations (ODEs) for the non-constant volume and the five components in the reactor. We extend the model with a glucose inhibition term to make the model feasible for optimization case studies. We formulate an optimization problem in terms of an optimal control problem (OCP) and consider four different setups for optimization. Compared to the base case, the optimal operation of the perfusion reactor increases the mAb yield with 44% when samples are taken from the reactor and with 52% without sampling. Additionally, our results show that multiple optimal feeding trajectories exist and that full glucose utilization can be forced without loss of mAb formation.

math.OC↗

arXiv2023

Regularity results for a class of nonlocal double phase equations with VMO coefficients

We study a class of nonlocal double phase problems with discontinuous coefficients. A local self-improving property and a higher Hölder continuity result for weak solutions to such problems are obtained under the assumptions that the associated coefficient functions are of type VMO (vanishing mean oscillation) and that the principal coefficient depends not only on the variables but also on the solution itself.

math.AP↗

arXiv2023

Peeling from a liquid

We establish the existence of a cusp in the curvature of a solid sheet at its contact with a liquid subphase. We study two configurations in floating sheets where the solid-vapor-liquid contact line is a straight line and a circle, respectively. In the former case, a rectangular sheet is lifted at its edge, whereas in the latter a gas bubble is injected beneath a floating sheet. We show that in both geometries the derivative of the sheet's curvature is discontinuous. We demonstrate that the boundary condition at the contact is identical in these two geometries, even though the shape of the contact line and the stress distribution in the sheet are sharply different.

cond-mat.soft↗

arXiv2023

Feasibility of the J-PET to monitor range of therapeutic proton beams

Objective: The aim of this work is to investigate the feasibility of the Jagiellonian Positron Emission Tomography (J-PET) scanner for intra-treatment proton beam range monitoring. Approach: The Monte Carlo simulation studies with GATE and PET image reconstruction with CASToR were performed in order to compare six J-PET scanner geometries (three dual-heads and three cylindrical). We simulated proton irradiation of a PMMA phantom with a Single Pencil Beam (SPB) and Spread-Out Bragg Peak (SOBP) of various ranges. The sensitivity and precision of each scanner were calculated, and considering the setup's cost-effectiveness, we indicated potentially optimal geometries for the J-PET scanner prototype dedicated to the proton beam range assessment. Main results: The investigations indicate that the double-layer cylindrical and triple-layer double-head configurations are the most promising for clinical application. We found that the scanner sensitivity is of the order of 10$^{-5}$ coincidences per primary proton, while the precision of the range assessment for both SPB and SOBP irradiation plans was found below 1 mm. Among the scanners with the same number of detector modules, the best results are found for the triple-layer dual-head geometry. Significance: We performed simulation studies demonstrating that the feasibility of the J-PET detector for PET-based proton beam therapy range monitoring is possible with reasonable sensitivity and precision enabling its pre-clinical tests in the clinical proton therapy environment. Considering the sensitivity, precision and cost-effectiveness, the double-layer cylindrical and triple-layer dual-head J-PET geometry configurations seem promising for the future clinical application. Experimental tests are needed to confirm these findings.

physics.med-ph↗