Tootfinder

🫥 Novel attack against virtually all VPN apps neuters their entire purpose
https://arstechnica.com/security/2024/05/novel-attack-against-virtually-all-vpn-apps-neuters-their-entire-purpose/

Novel attack against virtually all VPN apps neuters their entire purpose
TunnelVision vulnerability has existed since 2002 and may already be known to attackers.

Novel bionic glasses help the blind 'see' through sound https://www.medicalresearch.nsw.gov.au/novel-bionic-glasses-help-the-blind-see-through-sound/ No, this is not about

Novel bionic glasses help the blind ‘see’ through sound - NSW Health & Medical Research
When The Voice coaches all turned their chairs during Julee-Anne Bell’s 2021 audition, the blind, classically trained singer had no idea that Jessica Mauboy, had swivelled first. “I should probably let you know that I actually can’t see, I can’t see you at all,” explained Bell, 48, who has been without sight since birth. “There’s […]

Two novel pure-state coherence measures in quantifying coherence
Manis Hazra, Debabrata Goswami
https://arxiv.org/abs/2403.07146 https://

Two novel pure-state coherence measures in quantifying coherence
In the resource theory of coherence, the quantification of quantum-state coherence is an important task. In this regard, the key ingredients are the various coherence monotones (or measures). There are few coherence-monotone classes that solely depend on other coherence measures defined for all the pure states; in other words, they rely on the pure state coherence measures (PSCM). Here, we set forth two such novel PSCMs, and validate each of them through the fulfillment of all four necessary co…

lesmis: Les Misérables coappearances
The network of scene coappearances of characters in Victor Hugo's novel "Les Miserables". Edge weights denote the number of such occurrences.
This network has 77 nodes and 254 edges.
Tags: Social, Fictional, Weighted
https://networks.skewed.de/net/lesmis<…

Do bird angels have four wings?
Harold, a character in a novel by Steven Wright, the comedian.

Large, Small or Both: A Novel Data Augmentation Framework Based on Language Models for Debiasing Opinion Summarization
Yanyue Zhang, Pengfei Li, Yilong Lai, Deyu Zhou
https://arxiv.org/abs/2403.07693

Large, Small or Both: A Novel Data Augmentation Framework Based on Language Models for Debiasing Opinion Summarization
As more than 70$\%$ of reviews in the existing opinion summary data set are positive, current opinion summarization approaches are reluctant to generate negative summaries given the input of negative texts. To address such sentiment bias, a direct approach without the over-reliance on a specific framework is to generate additional data based on large language models to balance the emotional distribution of the dataset. However, data augmentation based on large language models faces two disadvan…

My wife sent me a calendar invite to something called "Kittentits" and I assumed it was a punk band but supposedly it's a new novel by one of her colleagues and we'll be going to a reading.
➡️ https://www.goodreads.com/en/book/show/196841905

Kittentits
A feral, heart-busting, absurdist debut about Molly, a …

novel-writer 2.0.0をリリースしました。
.mdの拡張子を持つファイルも扱えるようになります。
#を使う見出しでアウトラインのように折りたたむこともできるようになりました

novel-writer - Visual Studio Marketplace
Extension for Visual Studio Code - VS Codeの小説執筆を支援する機能拡張です

"There is a tendency for media coverage to focus on the source of this imagery, because generative AI is a novel technology that many people are still trying to wrap their head around. But that fact obscures the reason the images are relevant: They spread on social-media networks."
#generativeAI #ai #socialmedia
https://www.theatlantic.com/technology/archive/2024/03/generative-ai-social-media-moderation/677730/

Advancing Security in AI Systems: A Novel Approach to Detecting Backdoors in Deep Neural Networks
Khondoker Murad Hossain, Tim Oates
https://arxiv.org/abs/2403.08208

Advancing Security in AI Systems: A Novel Approach to Detecting Backdoors in Deep Neural Networks
In the rapidly evolving landscape of communication and network security, the increasing reliance on deep neural networks (DNNs) and cloud services for data processing presents a significant vulnerability: the potential for backdoors that can be exploited by malicious actors. Our approach leverages advanced tensor decomposition algorithms Independent Vector Analysis (IVA), Multiset Canonical Correlation Analysis (MCCA), and Parallel Factor Analysis (PARAFAC2) to meticulously analyze the weights …

🏈 @… #NFL
Via ANTIFAldo @ANTIFAldo
·
16s
“It’s Week 7, the New York Jets are 2-4, and their starting quarterback is running for Vice President” is the plot of a Mike Lupica novel

I reread The Hour of the Thin Ox by Colin Greenland over the past few days. It's a picaresque novel that unpacks layers upon layers of culture, in opposition and composition with mutual ignorance between the three major cultures.
One of those cultures is part goat part hominid and seems the most primitive yet by using the environment around them they have all of the benefits of a technological culture without some of the drawbacks, but are at the right time as barbarous as the othe…

RobotCycle: Assessing Cycling Safety in Urban Environments
Efimia Panagiotaki, Tyler Reinmund, Brian Liu, Stephan Mouton, Luke Pitt, Arundathi Shaji Shanthini, Matthew Towlson, Wayne Tubby, Chris Prahacs, Daniele De Martini, Lars Kunze
https://arxiv.org/abs/2403.07789

RobotCycle: Assessing Cycling Safety in Urban Environments
This paper introduces RobotCycle, a novel ongoing project that leverages Autonomous Vehicle (AV) research to investigate how cycling infrastructure influences cyclist behaviour and safety during real-world journeys. The project's requirements were defined in collaboration with key stakeholders (i.e. city planners, cyclists, and policymakers), informing the design of risk and safety metrics and the data collection criteria. We propose a data-driven approach relying on a novel, rich dataset of di…

Novel Signatures of Radiation Reaction in Electron-Laser Sidescattering
Philipp Sikorski, Alec G. R. Thomas, Stepan S. Bulanov, Matt Zepf, Daniel Seipt
https://arxiv.org/abs/2403.07455

Novel Signatures of Radiation Reaction in Electron-Laser Sidescattering
In this article we investigate novel signatures of radiation reaction via the angular deflection of an electron beam colliding at 90 degrees with an intense laser pulse. Due to the radiation reaction effect, the electrons can be deflected towards the beam axis for plane wave backgrounds, which is not possible in the absence of radiation reaction effects. The magnitude and size of the deflection angle can be controlled by tailoring the laser pulse shapes. The effect is first derived analytically…

Beyond Pi Day, today is the 6-year anniversary of the assassination of Marielle Franco, a Brazilian left-wing politician murdered under Bolsonaro. The Wikipedia page reads like a novel, with cover-ups, suspicious circumstances, and one suspect group's (verified) alibi being, I kid you not, "We were busy killing someone else at the time".

A novel fast iterative moment method for near-continuum flows
Guanghan Li, Chunwu Wang, Zhicheng Hu
https://arxiv.org/abs/2403.07358 https://

A novel fast iterative moment method for near-continuum flows
In this paper, we develop a novel fast iterative moment method for the steady-state simulation of near-continuum flows, which are modeled by the high-order moment system derived from the Boltzmann-BGK equation. The fast convergence of the present method is mainly achieved by alternately solving the moment system and the hydrodynamic equations with compatible constitutive relations and boundary conditions. To be specific, the compatible hydrodynamic equations are solved in each iteration to get …

Researchers say they haven't found "strikingly novel compounds" after analyzing a subset of the 2.2M new crystals DeepMind claimed its AI tool GNoMe discovered (Jason Koebler/404 Media)
https://www.404media.co/google-says-it-dis

Is Google's AI Actually Discovering 'Millions of New Materials?'
"In the DeepMind paper there are many examples of predicted materials that are clearly nonsensical."

A Novel Pseudo Nearest Neighbor Classification Method Using Local Harmonic Mean Distance
Junzhuo Chen, Zhixin Lu
https://arxiv.org/abs/2405.06238 https://<…

NYTimes: Gabriel García Mšrquez Wanted to Destroy His Last Novel. It’s About to Be Published.
Gabriel García Mšrquez Wanted to Destroy His Last Novel. It’s About to Be Published. https://www.nytimes.com/2024/03/06/books/g

Gabriel García Márquez Wanted to Destroy His Last Novel. It’s About to Be Published.
The publication of “Until August” adds a surprising twist to his legacy, and may stir questions about posthumous releases that contradict a writer’s directives.

lesmis: Les Misérables coappearances
The network of scene coappearances of characters in Victor Hugo's novel "Les Miserables". Edge weights denote the number of such occurrences.
This network has 77 nodes and 254 edges.
Tags: Social, Fictional, Weighted
https://networks.skewed.de/net/lesmis<…

I’m always enamored with side-channel attacks. Pulling data from unexpected sources is fascinating and difficult to predict.
This isn’t particularly novel — padding data to hide length is part of the toolbox — but new systems making old mistakes is also fun!
https://<…

Hackers can read private AI-assistant chats even though they’re encrypted
All non-Google chat GPTs affected by side channel that leaks responses sent to users.

This https://arxiv.org/abs/2404.06710 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

SpikeNVS: Enhancing Novel View Synthesis from Blurry Images via Spike Camera
One of the most critical factors in achieving sharp Novel View Synthesis (NVS) using neural field methods like Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) is the quality of the training images. However, Conventional RGB cameras are susceptible to motion blur. In contrast, neuromorphic cameras like event and spike cameras inherently capture more comprehensive temporal information, which can provide a sharp representation of the scene as additional training data. Recent methods…

Novel Active Sensing and Inference for mmWave Beam Alignment Using Single RF Chain Systems
Rohan R. Pote, Bhaskar D. Rao
https://arxiv.org/abs/2404.07604 h…

Novel Active Sensing and Inference for mmWave Beam Alignment Using Single RF Chain Systems
We propose a novel sensing approach for the beam alignment problem in millimeter wave systems using a single Radio Frequency (RF) chain. Conventionally, beam alignment using a single phased array involves comparing beamformer output power across different spatial regions. This incurs large training overhead due to the need to perform the beam scan operation. The proposed Synthesis of Virtual Array Manifold (SVAM) sensing methodology is inspired from synthetic aperture radar systems and realizes…

The world of Falural is in peril, but the emergence of four champions brings a glimmer of hope. Through their journey, they will discover unexpected allies and unlock their true potential. Will they be able to save Falural before it's too late?
Champions of Falural, a fantasy adventure novel by Linda Teppler
#writing

Do bird angels have four wings?
Harold, a character in a novel by Steven Wright, the comedian.

Large, Small or Both: A Novel Data Augmentation Framework Based on Language Models for Debiasing Opinion Summarization
Yanyue Zhang, Pengfei Li, Yilong Lai, Deyu Zhou
https://arxiv.org/abs/2403.07693

Large, Small or Both: A Novel Data Augmentation Framework Based on Language Models for Debiasing Opinion Summarization
As more than 70$\%$ of reviews in the existing opinion summary data set are positive, current opinion summarization approaches are reluctant to generate negative summaries given the input of negative texts. To address such sentiment bias, a direct approach without the over-reliance on a specific framework is to generate additional data based on large language models to balance the emotional distribution of the dataset. However, data augmentation based on large language models faces two disadvan…

My wife sent me a calendar invite to something called "Kittentits" and I assumed it was a punk band but supposedly it's a new novel by one of her colleagues and we'll be going to a reading.
➡️ https://www.goodreads.com/en/book/show/196841905

Kittentits
A feral, heart-busting, absurdist debut about Molly, a …

Novel first-order phase transition and critical points in SU(3) Yang-Mills theory with spatial compactification
Daisuke Fujii, Akihiro Iwanaka, Masakiyo Kitazawa, Daiki Suenaga
https://arxiv.org/abs/2404.07899

Novel first-order phase transition and critical points in SU(3) Yang-Mills theory with spatial compactification
We investigate the thermodynamics and phase structure of $SU(3)$ Yang-Mills theory on $\mathbb{T}^2\times\mathbb{R}^2$ in Euclidean spacetime in an effective-model approach. The model incorporates two Polyakov loops along two compactified directions as dynamical variables, and is constructed to reproduce thermodynamics on $\mathbb{T}^2\times\mathbb{R}^2$ measured on the lattice. The model analysis indicates the existence of a novel first-order phase transition on $\mathbb{T}^2\times\mathbb{R}^2…

This https://arxiv.org/abs/2209.13725 has been replaced.
link: https://scholar.google.com/scholar?q=a

On the Descriptive Complexity of Groups without Abelian Normal Subgroups
In this paper, we explore the descriptive complexity theory of finite groups by examining the power of the second Ehrenfeucht-Fraïssé bijective pebble game in Hella's (Ann. Pure Appl. Log., 1989) heirarchy. This is a Spoiler-Duplicator game in which Spoiler can place up to two pebbles each round. While it trivially solves graph isomorphism, it may be nontrivial for finite groups, and other ternary relational structures. We first provide a novel generalization of Weisfeiler-Leman (WL) coloring…

Relevance Score: A Landmark-Like Heuristic for Planning
Oliver Kim, Mohan Sridharan
https://arxiv.org/abs/2403.07510 https://arxiv.or…

Relevance Score: A Landmark-Like Heuristic for Planning
Landmarks are facts or actions that appear in all valid solutions of a planning problem. They have been used successfully to calculate heuristics that guide the search for a plan. We investigate an extension to this concept by defining a novel "relevance score" that helps identify facts or actions that appear in most but not all plans to achieve any given goal. We describe an approach to compute this relevance score and use it as a heuristic in the search for a plan. We experimentally compare t…

A novel Bayesian approach for decomposing the radio emission of quasars: I. Modelling the radio excess in red quasars
B. -H. Yue, P. N. Best, K. J. Duncan, G. Calistro-Rivera, L. K. Morabito, J. W. Petley, I. Prandoni, H. J. A. R\"ottgering, D. J. B. Smith
https://arxiv.org/abs/2403.07074

A novel Bayesian approach for decomposing the radio emission of quasars: I. Modelling the radio excess in red quasars
Studies show that both radio jets from the active galactic nuclei (AGN) and the star formation (SF) activity in quasar host galaxies contribute to the quasar radio emission; yet their relative contributions across the population remain unclear. Here, we present an improved parametric model that allows us to statistically separate the SF and AGN components in observed quasar radio flux density distributions, and investigate how their relative contributions evolve with AGN bolometric luminosity (…

A Novel Method to Constrain Tidal Quality Factor from A Non-synchronized Exoplanetary System
Takato Tokuno, Akihiko Fukui, Takeru K. Suzuki
https://arxiv.org/abs/2403.07375

A Novel Method to Constrain Tidal Quality Factor from A Non-synchronized Exoplanetary System
We propose a novel method to constrain the tidal quality factor, $Q'$, from a non-synchronized star-planet system consisting of a slowly rotating low-mass star and a close-in Jovian planet, taking into account the tidal interaction and the magnetic braking. On the basis of dynamical system theory, the track of the co-evolution of angular momentum for such a system exhibits the existence of a forbidden region in the $Ω_\mathrm{orb}$ -- $Ω_\mathrm{spin}$ plane , where $Ω_\mathrm{spin}$ and $Ω…

"There is a tendency for media coverage to focus on the source of this imagery, because generative AI is a novel technology that many people are still trying to wrap their head around. But that fact obscures the reason the images are relevant: They spread on social-media networks."
#generativeAI #ai #socialmedia
https://www.theatlantic.com/technology/archive/2024/03/generative-ai-social-media-moderation/677730/

Ett protein som fungerar som sötningsmedel. Intressant för framtiden.
Godkänt direkt i USA eftersom det anses vara "naturligt" och därmed safe 🤷‍♂️
FDA’s ‘no questions’ letter for Oobli’s sweet protein opens doors for international expansion

FDA’s ‘no questions’ letter for Oobli’s sweet protein opens doors for international expansion
FDA’s recent acknowledgement that low-sugar tea and chocolate maker Oobli’s novel sweet protein sourced from the Oubli fruit and produced via precision fermentation is Generally Recognized As Safe will grease the rails for the California-based company to expand internationally, CEO Ali Wing told FoodNavigator-USA.

COSTREAM: Learned Cost Models for Operator Placement in Edge-Cloud Environments
Roman Heinrich, Carsten Binnig, Harald Kornmayer, Manisha Luthra
https://arxiv.org/abs/2403.08444 <…

COSTREAM: Learned Cost Models for Operator Placement in Edge-Cloud Environments
In this work, we present COSTREAM, a novel learned cost model for Distributed Stream Processing Systems that provides accurate predictions of the execution costs of a streaming query in an edge-cloud environment. The cost model can be used to find an initial placement of operators across heterogeneous hardware, which is particularly important in these environments. In our evaluation, we demonstrate that COSTREAM can produce highly accurate cost estimates for the initial operator placement and e…

books :-)
Been reading a few actual books!
Latest review over at @… was of a science fiction novel by Emily Tesh, which I'm still thinking about - v good.
#books #BookReviews

This https://arxiv.org/abs/2312.03690 has been replaced.
initial toot: https://mastoxiv.page/@a…

Inverse Design of Vitrimeric Polymers by Molecular Dynamics and Generative Modeling
Vitrimer is a new class of sustainable polymers with the ability of self-healing through rearrangement of dynamic covalent adaptive networks. However, a limited choice of constituent molecules restricts their property space, prohibiting full realization of their potential applications. Through a combination of molecular dynamics (MD) simulations and machine learning (ML), particularly a novel graph variational autoencoder (VAE) model, we establish a method for generating novel vitrimers and gui…

This https://arxiv.org/abs/2208.03467 has been replaced.
link: https://scholar.google.com/scholar?q=a

Real-time Neural Dense Elevation Mapping for Urban Terrain with Uncertainty Estimations
Having good knowledge of terrain information is essential for improving the performance of various downstream tasks on complex terrains, especially for the locomotion and navigation of legged robots. We present a novel framework for neural urban terrain reconstruction with uncertainty estimations. It generates dense robot-centric elevation maps online from sparse LiDAR observations. We design a novel pre-processing and point features representation approach that ensures high robustness and comp…

This https://arxiv.org/abs/2401.15211 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Charged Black Holes with Yukawa Potential
This study derives a novel family of charged black hole solutions featuring short- and long-range modifications. These ones are achieved through a Yukawa-like gravitational potential modification and a nonsingular electric potential incorporation. The short-range corrections encode quantum gravity effects, while the long-range adjustments simulate gravitational effects akin to those attributed to dark matter. Our investigation reveals that the total mass of the black hole undergoes corrections …

Configuration spaces of orbits and their $S_n$-equivariant $E$-polynomials
Alejandro Calleja
https://arxiv.org/abs/2403.07765 https://

Configuration spaces of orbits and their $S_n$-equivariant $E$-polynomials
In this paper, we introduce the configuration space of orbits, a generalization of the configuration space of points but for algebraic varieties that are acted by an algebraic reductive group. We develop a novel method for computing the $S_n$-equivariant $E$-polynomial of an algebraic variety, and we apply it to this new kind of varieties.

lesmis: Les Misérables coappearances
The network of scene coappearances of characters in Victor Hugo's novel "Les Miserables". Edge weights denote the number of such occurrences.
This network has 77 nodes and 254 edges.
Tags: Social, Fictional, Weighted
https://networks.skewed.de/net/lesmis<…

Designing Wearable Augmented Reality Concepts to Support Scalability in Autonomous Vehicle-Pedestrian Interaction
Tram Thi Minh Tran, Callum Parker, Yiyuan Wang, Martin Tomitsch
https://arxiv.org/abs/2403.07006

Designing Wearable Augmented Reality Concepts to Support Scalability in Autonomous Vehicle-Pedestrian Interaction
Wearable augmented reality (AR) offers new ways for supporting the interaction between autonomous vehicles (AVs) and pedestrians due to its ability to integrate timely and contextually relevant data into the user's field of view. This article presents novel wearable AR concepts that assist crossing pedestrians in multi-vehicle scenarios where several AVs frequent the road from both directions. Three concepts with different communication approaches for signaling responses from multiple AVs to a …

Large language models surpass human experts in predicting neuroscience results https://arxiv.org/abs/2403.03230 Well, let LLMs predict results with sensory substitution training then.

Large language models surpass human experts in predicting neuroscience results
Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution. LLMs trained on the vast scientific literature could potentially integrate noisy yet interrelated findings to forecast novel results better than human experts. To evaluate this possibility, we created BrainBench, a forward-looking benchmark for predicting neuroscience results. We find that LLMs surpass e…

RA-ICM: A Novel Independent Cascade Model Incorporating User Relationships and Attitudes
Xinyu Li, Yutong Guo, Jixuan He, Jiacheng Zhao, Chenwei Wang
https://arxiv.org/abs/2403.06385

RA-ICM: A Novel Independent Cascade Model Incorporating User Relationships and Attitudes
The rapid development of social networks has a wide range of social effects, which facilitates the study of social issues. Accurately forecasting the information propagation process within social networks is crucial for promptly understanding the event direction and effectively addressing social problems in a scientific manner. The relationships between non-adjacent users and the attitudes of users significantly influence the information propagation process within social networks. However, exis…

This https://arxiv.org/abs/2204.14100 has been replaced.
link: https://scholar.google.com/scholar?q=a

Adversarial Distortion Learning for Medical Image Denoising
We present a novel adversarial distortion learning (ADL) for denoising two- and three-dimensional (2D/3D) biomedical image data. The proposed ADL consists of two auto-encoders: a denoiser and a discriminator. The denoiser removes noise from input data and the discriminator compares the denoised result to its noise-free counterpart. This process is repeated until the discriminator cannot differentiate the denoised data from the reference. Both the denoiser and the discriminator are built upon a …

Mesh Refinement with Early Termination for Dynamic Feasibility Problems
Eduardo M. G. Vila, Eric C. Kerrigan, Paul Bruce
https://arxiv.org/abs/2403.07811 h…

Mesh Refinement with Early Termination for Dynamic Feasibility Problems
We propose a novel early-terminating mesh refinement strategy using an integrated residual method to solve dynamic feasibility problems. As a generalization of direct collocation, the integrated residual method is used to approximate an infinite-dimensional problem into a sequence of finite-dimensional optimization subproblems. Each subproblem in the sequence is a finer approximation of the previous. It is shown that these subproblems need not be solved to a high precision; instead, an early te…

An improvement of degree-based hashing (DBH) graph partition method, using a novel metric
Anna Mastikhina, Oleg Senkevich, Dmitry Sirotkin, Danila Demin, Stanislav Moiseev
https://arxiv.org/abs/2404.07624

An improvement of degree-based hashing (DBH) graph partition method, using a novel metric
This paper examines the graph partition problem and introduces a new metric, MSIDS (maximal sum of inner degrees squared). We establish its connection to the replication factor (RF) optimization, which has been the main focus of theoretical work in this field. Additionally, we propose a new partition algorithm, DBH-X, based on the DBH partitioner. We demonstrate that DBH-X significantly improves both the RF and MSIDS, compared to the baseline DBH algorithm. In addition, we provide test results …

Achievable Rate Analysis and Optimization of Double-RIS Assisted Spatially Correlated MIMO with Statistical CSI
Kaizhe Xu, Jiajia Guo, Jun Zhang, Shi Jin, Shaodan Ma
https://arxiv.org/abs/2403.07274

Achievable Rate Analysis and Optimization of Double-RIS Assisted Spatially Correlated MIMO with Statistical CSI
Reconfigurable intelligent surface (RIS) is a novel meta-material which can form a smart radio environment by dynamically altering reflection directions of the impinging electromagnetic waves. In the prior literature, the inter-RIS links which also contribute to the performance of the whole system are usually neglected when multiple RISs are deployed. In this paper we investigate a general double-RIS assisted multiple-input multiple-output (MIMO) wireless communication system under spatially co…

System Design Approach for Control of Differentially Private Dynamical Systems
Raman Goyal, Dhrubajit Chowdhury, Shantanu Rane
https://arxiv.org/abs/2403.08065

System Design Approach for Control of Differentially Private Dynamical Systems
This paper introduces a novel approach to concurrently design dynamic controllers and correlated differential privacy noise in dynamic control systems. An increase in privacy noise increases the system's privacy but adversely affects the system's performance. Our approach optimizes the noise distribution while shaping closed-loop system dynamics such that the privacy noise has the least impact on system performance and the most effect on system privacy. We further add privacy noise to both cont…

Beyond Random Inputs: A Novel ML-Based Hardware Fuzzing
Mohamadreza Rostami, Marco Chilese, Shaza Zeitouni, Rahul Kande, Jeyavijayan Rajendran, Ahmad-Reza Sadeghi
https://arxiv.org/abs/2404.06856

Beyond Random Inputs: A Novel ML-Based Hardware Fuzzing
Modern computing systems heavily rely on hardware as the root of trust. However, their increasing complexity has given rise to security-critical vulnerabilities that cross-layer at-tacks can exploit. Traditional hardware vulnerability detection methods, such as random regression and formal verification, have limitations. Random regression, while scalable, is slow in exploring hardware, and formal verification techniques are often concerned with manual effort and state explosions. Hardware fuzzi…

This https://arxiv.org/abs/2307.02037 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Reverse Diffusion Monte Carlo
We propose a Monte Carlo sampler from the reverse diffusion process. Unlike the practice of diffusion models, where the intermediary updates -- the score functions -- are learned with a neural network, we transform the score matching problem into a mean estimation one. By estimating the means of the regularized posterior distributions, we derive a novel Monte Carlo sampling algorithm called reverse diffusion Monte Carlo (rdMC), which is distinct from the Markov chain Monte Carlo (MCMC) methods.…

A novel instability in an elastoviscoplastic fluid flow
Ramkarn Patne
https://arxiv.org/abs/2405.07078 https://arxiv.org/pdf/2405.070…

adjnoun: Word adjacencies of David Copperfield
A network of word adjacencies of common adjectives and nouns in the novel "David Copperfield" by Charles Dickens.
This network has 112 nodes and 425 edges.
Tags: Informational, Language, Unweighted
https://networks.skewed.de/net/adjnoun

This https://arxiv.org/abs/2404.07122 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Driver Attention Tracking and Analysis
We propose a novel method to estimate a driver's points-of-gaze using a pair of ordinary cameras mounted on the windshield and dashboard of a car. This is a challenging problem due to the dynamics of traffic environments with 3D scenes of unknown depths. This problem is further complicated by the volatile distance between the driver and the camera system. To tackle these challenges, we develop a novel convolutional network that simultaneously analyzes the image of the scene and the image of the…

A Novel Optimization-Based Collision Avoidance For Autonomous On-Orbit Assembly
Siavash Tavana, Sepideh Faghihi, Anton de Ruiter, Krishna Dev Kumar
https://arxiv.org/abs/2404.07916

A Novel Optimization-Based Collision Avoidance For Autonomous On-Orbit Assembly
The collision avoidance constraints are prominent as non-convex, non-differentiable, and challenging when defined in optimization-based motion planning problems. To overcome these issues, this paper presents a novel non-conservative collision avoidance technique using the notion of convex optimization to establish the distance between robotic spacecraft and space structures for autonomous on-orbit assembly operations. The proposed technique defines each ellipsoidal- and polyhedral-shaped object…

Relevance Score: A Landmark-Like Heuristic for Planning
Oliver Kim, Mohan Sridharan
https://arxiv.org/abs/2403.07510 https://arxiv.or…

Relevance Score: A Landmark-Like Heuristic for Planning
Landmarks are facts or actions that appear in all valid solutions of a planning problem. They have been used successfully to calculate heuristics that guide the search for a plan. We investigate an extension to this concept by defining a novel "relevance score" that helps identify facts or actions that appear in most but not all plans to achieve any given goal. We describe an approach to compute this relevance score and use it as a heuristic in the search for a plan. We experimentally compare t…

Researchers detail an attack against many VPN apps that force them to send some or all traffic outside of the VPN encrypted tunnel; Android mitigates the flaw (Dan Goodin/Ars Technica)
https://arstechnica.com/security/2024/

Novel attack against virtually all VPN apps neuters their entire purpose
TunnelVision vulnerability has existed since 2002 and may already be known to attackers.

This https://arxiv.org/abs/2401.10679 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Coherent Control of the Fine-Structure Qubit in a Single Alkaline-Earth Atom
We report on the first realization of a novel neutral atom qubit encoded in the metastable fine-structure states ${^3\rm{P}_0}$ and ${^3\rm{P}_2}$ of single $^{88}$Sr atoms trapped in an optical tweezer. Raman coupling of the qubit states promises rapid single-qubit rotations on par with the fast Rydberg-mediated two-body gates. We demonstrate preparation, read-out, and coherent control of the qubit. In addition to driving Rabi oscillations bridging an energy gap of more than 17 THz using a pai…

Efficient Fault Tolerance for Pipelined Query Engines via Write-ahead Lineage
Ziheng Wang, Alex Aiken
https://arxiv.org/abs/2403.08062 https://

Efficient Fault Tolerance for Pipelined Query Engines via Write-ahead Lineage
Modern distributed pipelined query engines either do not support intra-query fault tolerance or employ high-overhead approaches such as persisting intermediate outputs or checkpointing state. In this work, we present write-ahead lineage, a novel fault recovery technique that combines Spark's lineage-based replay and write-ahead logging. Unlike Spark, where the lineage is determined before query execution, write-ahead lineage persistently logs lineage at runtime to support dynamic task dependenc…

Releasing novel-writer 1.9.19
- PDFを作成する際に、自動縦中横が複数あるとカーソルの除去に失敗することがあるバグを修正しました
- はおこっこ @haoblackj@x.com さん、ありがとうございます
#novelwriter
https://marketplace.vi…

novel-writer - Visual Studio Marketplace
Extension for Visual Studio Code - VS Codeの小説執筆を支援する機能拡張です

This https://arxiv.org/abs/2311.08758 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

A Novel Tree Model-based DNN to Achieve a High-Resolution DOA Estimation via Massive MIMO receive array
To satisfy the high-resolution requirements of direction-of-arrival (DOA) estimation, conventional deep neural network (DNN)-based methods using grid idea need to significantly increase the number of output classifications and also produce a huge high model complexity. To address this problem, a multi-level tree-based DNN model (TDNN) is proposed as an alternative, where each level takes small-scale multi-layer neural networks (MLNNs) as nodes to divide the target angular interval into multiple…

Supporting Annotators with Affordances for Efficiently Labeling Conversational Data
Austin Z. Henley, David Piorkowski
https://arxiv.org/abs/2403.07762 htt…

Supporting Annotators with Affordances for Efficiently Labeling Conversational Data
Without well-labeled ground truth data, machine learning-based systems would not be as ubiquitous as they are today, but these systems rely on substantial amounts of correctly labeled data. Unfortunately, crowdsourced labeling is time consuming and expensive. To address the concerns of effort and tedium, we designed CAL, a novel interface to aid in data labeling. We made several key design decisions for CAL, which include preventing inapt labels from being selected, guiding users in selecting a…

Mesh Refinement with Early Termination for Dynamic Feasibility Problems
Eduardo M. G. Vila, Eric C. Kerrigan, Paul Bruce
https://arxiv.org/abs/2403.07811 h…

Mesh Refinement with Early Termination for Dynamic Feasibility Problems
We propose a novel early-terminating mesh refinement strategy using an integrated residual method to solve dynamic feasibility problems. As a generalization of direct collocation, the integrated residual method is used to approximate an infinite-dimensional problem into a sequence of finite-dimensional optimization subproblems. Each subproblem in the sequence is a finer approximation of the previous. It is shown that these subproblems need not be solved to a high precision; instead, an early te…

Review of Generative AI Methods in Cybersecurity
Yagmur Yigit, William J Buchanan, Madjid G Tehrani, Leandros Maglaras
https://arxiv.org/abs/2403.08701 htt…

Review of Generative AI Methods in Cybersecurity
Large language models (LLMs) and generative artificial intelligence (GenAI) constitute paradigm shifts in cybersecurity that present hitherto unseen challenges as well as opportunities. In examining the state-of-the-art application of GenAI in cybersecurity, this work highlights how models like Google's Gemini and ChatGPT-4 potentially enhance security protocols, vulnerability assessment, and threat identification. Our research highlights the significance of a novel approach that employs LLMs t…

System Design Approach for Control of Differentially Private Dynamical Systems
Raman Goyal, Dhrubajit Chowdhury, Shantanu Rane
https://arxiv.org/abs/2403.08065

System Design Approach for Control of Differentially Private Dynamical Systems
This paper introduces a novel approach to concurrently design dynamic controllers and correlated differential privacy noise in dynamic control systems. An increase in privacy noise increases the system's privacy but adversely affects the system's performance. Our approach optimizes the noise distribution while shaping closed-loop system dynamics such that the privacy noise has the least impact on system performance and the most effect on system privacy. We further add privacy noise to both cont…

This https://arxiv.org/abs/2403.06242 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

COVID-19 Computer-aided Diagnosis through AI-assisted CT Imaging Analysis: Deploying a Medical AI System
Computer-aided diagnosis (CAD) systems stand out as potent aids for physicians in identifying the novel Coronavirus Disease 2019 (COVID-19) through medical imaging modalities. In this paper, we showcase the integration and reliable and fast deployment of a state-of-the-art AI system designed to automatically analyze CT images, offering infection probability for the swift detection of COVID-19. The suggested system, comprising both classification and segmentation components, is anticipated to re…

Thought Graph: Generating Thought Process for Biological Reasoning
Chi-Yang Hsu, Kyle Cox, Jiawei Xu, Zhen Tan, Tianhua Zhai, Mengzhou Hu, Dexter Pratt, Tianlong Chen, Ziniu Hu, Ying Ding
https://arxiv.org/abs/2403.07144

Thought Graph: Generating Thought Process for Biological Reasoning
We present the Thought Graph as a novel framework to support complex reasoning and use gene set analysis as an example to uncover semantic relationships between biological processes. Our framework stands out for its ability to provide a deeper understanding of gene sets, significantly surpassing GSEA by 40.28% and LLM baselines by 5.38% based on cosine similarity to human annotations. Our analysis further provides insights into future directions of biological processes naming, and implications …

Angular momentum sensitivities in scalar-tensor theories
Adrien Kuntz, Enrico Barausse
https://arxiv.org/abs/2403.07980 https://arxiv…

Angular momentum sensitivities in scalar-tensor theories
Scalar-tensor theories have a long history as possible phenomenological alternatives to General Relativity, but are known to potentially produce deviations from the (strong) equivalence principle in systems involving self-gravitating objects, as a result of the presence of an additional gravitational scalar field besides the tensor modes of General Relativity. We describe here a novel mechanism whereby the equivalence principle is violated for an isolated rotating neutron star, if the gravitati…

This https://arxiv.org/abs/2403.18551 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Attention Calibration for Disentangled Text-to-Image Personalization
Recent thrilling progress in large-scale text-to-image (T2I) models has unlocked unprecedented synthesis quality of AI-generated content (AIGC) including image generation, 3D and video composition. Further, personalized techniques enable appealing customized production of a novel concept given only several images as reference. However, an intriguing problem persists: Is it possible to capture multiple, novel concepts from one single reference image? In this paper, we identify that existing appr…

This https://arxiv.org/abs/2310.18554 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
Logistic bandit is a ubiquitous framework of modeling users' choices, e.g., click vs. no click for advertisement recommender system. We observe that the prior works overlook or neglect dependencies in $S \geq \lVert θ_\star \rVert_2$, where $θ_\star \in \mathbb{R}^d$ is the unknown parameter vector, which is particularly problematic when $S$ is large, e.g., $S \geq d$. In this work, we improve the dependency on $S$ via a novel approach called {\it regret-to-confidence set conversion (R2CS)}, …

This https://arxiv.org/abs/2306.06986 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Multilevel leapfrogging initialization for quantum approximate optimization algorithm
Recently, Zhou et al. have proposed a novel Interpolation-based (INTERP) strategy to generate the initial parameters for the Parameterized Quantum Circuit (PQC) in Quantum Approximate Optimization Algorithm (QAOA). INTERP produces the guess of the initial parameters at level $i+1$ by applying linear interpolation to the optimized parameters at level $i$, achieving better performance than random initialization (RI). Nevertheless, INTERP consumes extensive running costs for deep QAOA because it n…

Thought Graph: Generating Thought Process for Biological Reasoning
Chi-Yang Hsu, Kyle Cox, Jiawei Xu, Zhen Tan, Tianhua Zhai, Mengzhou Hu, Dexter Pratt, Tianlong Chen, Ziniu Hu, Ying Ding
https://arxiv.org/abs/2403.07144

Thought Graph: Generating Thought Process for Biological Reasoning
We present the Thought Graph as a novel framework to support complex reasoning and use gene set analysis as an example to uncover semantic relationships between biological processes. Our framework stands out for its ability to provide a deeper understanding of gene sets, significantly surpassing GSEA by 40.28% and LLM baselines by 5.38% based on cosine similarity to human annotations. Our analysis further provides insights into future directions of biological processes naming, and implications …

Differential Privacy in Nonlinear Dynamical Systems with Tracking Performance Guarantees
Dhrubajit Chowdhury, Raman Goyal, Shantanu Rane
https://arxiv.org/abs/2403.08181

Differential Privacy in Nonlinear Dynamical Systems with Tracking Performance Guarantees
We introduce a novel approach to make the tracking error of a class of nonlinear systems differentially private in addition to guaranteeing the tracking error performance. We use funnel control to make the tracking error evolve within a performance funnel that is pre-specified by the user. We make the performance funnel differentially private by adding a bounded continuous noise generated from an Ornstein-Uhlenbeck-type process. Since the funnel controller is a function of the performance funne…

Advancements in Continuous Glucose Monitoring: Integrating Deep Learning and ECG Signal
MohammadReza Hosseinzadehketilateh, Banafsheh Adami, Nima Karimian
https://arxiv.org/abs/2403.07296

Advancements in Continuous Glucose Monitoring: Integrating Deep Learning and ECG Signal
This paper presents a novel approach to noninvasive hyperglycemia monitoring utilizing electrocardiograms (ECG) from an extensive database comprising 1119 subjects. Previous research on hyperglycemia or glucose detection using ECG has been constrained by challenges related to generalization and scalability, primarily due to using all subjects' ECG in training without considering unseen subjects as a critical factor for developing methods with effective generalization. We designed a deep neural …

This https://arxiv.org/abs/2311.11489 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A Universal Trust-Region Method for Convex and Nonconvex Optimization
This paper presents a universal trust-region method simultaneously incorporating quadratic regularization and the ball constraint. We introduce a novel mechanism to set the parameters in the proposed method that unifies the analysis for convex and nonconvex optimization. Our method exhibits an iteration complexity of $\tilde O(ε^{-3/2})$ to find an approximate second-order stationary point for nonconvex optimization. Meanwhile, the analysis reveals that the universal method attains an $O(ε^{-…

This https://arxiv.org/abs/2303.03360 has been replaced.
link: https://scholar.google.com/scholar?q=a

Improved Exploration for Safety-Embedded Differential Dynamic Programming Using Tolerant Barrier States
In this paper, we introduce Tolerant Discrete Barrier States (T-DBaS), a novel safety-embedding technique for trajectory optimization with enhanced exploratory capabilities. The proposed approach generalizes the standard discrete barrier state (DBaS) method by accommodating temporary constraint violation during the optimization process while still approximating its safety guarantees. Consequently, the proposed approach eliminates the DBaS's safe nominal trajectories assumption, while enhancing …

Flying With Photons: Rendering Novel Views of Propagating Light
Anagh Malik, Noah Juravsky, Ryan Po, Gordon Wetzstein, Kiriakos N. Kutulakos, David B. Lindell
https://arxiv.org/abs/2404.06493

Flying With Photons: Rendering Novel Views of Propagating Light
We present an imaging and neural rendering technique that seeks to synthesize videos of light propagating through a scene from novel, moving camera viewpoints. Our approach relies on a new ultrafast imaging setup to capture a first-of-its kind, multi-viewpoint video dataset with picosecond-level temporal resolution. Combined with this dataset, we introduce an efficient neural volume rendering framework based on the transient field. This field is defined as a mapping from a 3D point and 2D direc…

This https://arxiv.org/abs/2401.12248 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

A two-circuit approach to reducing quantum resources for the quantum lattice Boltzmann method
Computational fluid dynamics (CFD) simulations often entail a large computational burden on classical computers. At present, these simulations can require up to trillions of grid points and millions of time steps. To reduce costs, novel architectures like quantum computers may be intrinsically more efficient at the appropriate computation. Current quantum algorithms for solving CFD problems use a single quantum circuit and, in some cases, lattice-based methods. We introduce the a novel multiple…

GPT-generated Text Detection: Benchmark Dataset and Tensor-based Detection Method
Zubair Qazi, William Shiao, Evangelos E. Papalexakis
https://arxiv.org/abs/2403.07321

GPT-generated Text Detection: Benchmark Dataset and Tensor-based Detection Method
As natural language models like ChatGPT become increasingly prevalent in applications and services, the need for robust and accurate methods to detect their output is of paramount importance. In this paper, we present GPT Reddit Dataset (GRiD), a novel Generative Pretrained Transformer (GPT)-generated text detection dataset designed to assess the performance of detection models in identifying generated responses from ChatGPT. The dataset consists of a diverse collection of context-prompt pairs …

Differential Privacy in Nonlinear Dynamical Systems with Tracking Performance Guarantees
Dhrubajit Chowdhury, Raman Goyal, Shantanu Rane
https://arxiv.org/abs/2403.08181

Differential Privacy in Nonlinear Dynamical Systems with Tracking Performance Guarantees
We introduce a novel approach to make the tracking error of a class of nonlinear systems differentially private in addition to guaranteeing the tracking error performance. We use funnel control to make the tracking error evolve within a performance funnel that is pre-specified by the user. We make the performance funnel differentially private by adding a bounded continuous noise generated from an Ornstein-Uhlenbeck-type process. Since the funnel controller is a function of the performance funne…

Deep Learning-Assisted Parallel Interference Cancellation for Grant-Free NOMA in Machine-Type Communication
Yongjeong Oh, Jaehong Jo, Byonghyo Shim, Yo-Seb Jeon
https://arxiv.org/abs/2403.07255

Deep Learning-Assisted Parallel Interference Cancellation for Grant-Free NOMA in Machine-Type Communication
In this paper, we present a novel approach for joint activity detection (AD), channel estimation (CE), and data detection (DD) in uplink grant-free non-orthogonal multiple access (NOMA) systems. Our approach employs an iterative and parallel interference removal strategy inspired by parallel interference cancellation (PIC), enhanced with deep learning to jointly tackle the AD, CE, and DD problems. Based on this approach, we develop three PIC frameworks, each of which is designed for either cohe…

This https://arxiv.org/abs/2308.01758 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A Compliant Robotic Leg Based on Fibre Jamming
Humans possess a remarkable ability to react to unpredictable perturbations through immediate mechanical responses, which harness the visco-elastic properties of muscles to maintain balance. Inspired by this behaviour, we propose a novel design of a robotic leg utilising fibre jammed structures as passive compliant mechanisms to achieve variable joint stiffness and damping. We developed multi-material fibre jammed tendons with tunable mechanical properties, which can be 3D printed in one-go wit…

This https://arxiv.org/abs/2401.12248 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

A two-circuit approach to reducing quantum resources for the quantum lattice Boltzmann method
Computational fluid dynamics (CFD) simulations often entail a large computational burden on classical computers. At present, these simulations can require up to trillions of grid points and millions of time steps. To reduce costs, novel architectures like quantum computers may be intrinsically more efficient at the appropriate computation. Current quantum algorithms for solving CFD problems use a single quantum circuit and, in some cases, lattice-based methods. We introduce the a novel multiple…

GPT-generated Text Detection: Benchmark Dataset and Tensor-based Detection Method
Zubair Qazi, William Shiao, Evangelos E. Papalexakis
https://arxiv.org/abs/2403.07321

GPT-generated Text Detection: Benchmark Dataset and Tensor-based Detection Method
As natural language models like ChatGPT become increasingly prevalent in applications and services, the need for robust and accurate methods to detect their output is of paramount importance. In this paper, we present GPT Reddit Dataset (GRiD), a novel Generative Pretrained Transformer (GPT)-generated text detection dataset designed to assess the performance of detection models in identifying generated responses from ChatGPT. The dataset consists of a diverse collection of context-prompt pairs …

This https://arxiv.org/abs/2310.06169 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Synthesizing Robust Walking Gaits via Discrete-Time Barrier Functions with Application to Multi-Contact Exoskeleton Locomotion
Successfully achieving bipedal locomotion remains challenging due to real-world factors such as model uncertainty, random disturbances, and imperfect state estimation. In this work, we propose a novel metric for locomotive robustness -- the estimated size of the hybrid forward invariant set associated with the step-to-step dynamics. Here, the forward invariant set can be loosely interpreted as the region of attraction for the discrete-time dynamics. We illustrate the use of this metric towards …

Enhancing Quantum Variational Algorithms with Zero Noise Extrapolation via Neural Networks
Subhasree Bhattacharjee, Soumyadip Sarkar, Kunal Das, Bikramjit Sarkar
https://arxiv.org/abs/2403.07025

Enhancing Quantum Variational Algorithms with Zero Noise Extrapolation via Neural Networks
In the emergent realm of quantum computing, the Variational Quantum Eigensolver (VQE) stands out as a promising algorithm for solving complex quantum problems, especially in the noisy intermediate-scale quantum (NISQ) era. However, the ubiquitous presence of noise in quantum devices often limits the accuracy and reliability of VQE outcomes. This research introduces a novel approach to ameliorate this challenge by utilizing neural networks for zero noise extrapolation (ZNE) in VQE computations. …

Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
Dong Shu, Tianle Chen, Mingyu Jin, Yiting Zhang, Mengnan Du, Yongfeng Zhang
https://arxiv.org/abs/2403.07311

Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
The task of predicting multiple links within knowledge graphs (KGs) stands as a challenge in the field of knowledge graph analysis, a challenge increasingly resolvable due to advancements in natural language processing (NLP) and KG embedding techniques. This paper introduces a novel methodology, the Knowledge Graph Large Language Model Framework (KG-LLM), which leverages pivotal NLP paradigms, including chain-of-thought (CoT) prompting and in-context learning (ICL), to enhance multi-hop link pr…

This https://arxiv.org/abs/2311.16916 has been replaced.
link: https://scholar.google.com/scholar?q=a

Stein Variational Belief Propagation for Multi-Robot Coordination
Decentralized coordination for multi-robot systems involves planning in challenging, high-dimensional spaces. The planning problem is particularly challenging in the presence of obstacles and different sources of uncertainty such as inaccurate dynamic models and sensor noise. In this paper, we introduce Stein Variational Belief Propagation (SVBP), a novel algorithm for performing inference over nonparametric marginal distributions of nodes in a graph. We apply SVBP to multi-robot coordination b…

Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
Dong Shu, Tianle Chen, Mingyu Jin, Yiting Zhang, Mengnan Du, Yongfeng Zhang
https://arxiv.org/abs/2403.07311

Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
The task of predicting multiple links within knowledge graphs (KGs) stands as a challenge in the field of knowledge graph analysis, a challenge increasingly resolvable due to advancements in natural language processing (NLP) and KG embedding techniques. This paper introduces a novel methodology, the Knowledge Graph Large Language Model Framework (KG-LLM), which leverages pivotal NLP paradigms, including chain-of-thought (CoT) prompting and in-context learning (ICL), to enhance multi-hop link pr…

Rethinking ASTE: A Minimalist Tagging Scheme Alongside Contrastive Learning
Qiao Sun, Liujia Yang, Minghao Ma, Nanyang Ye, Qinying Gu
https://arxiv.org/abs/2403.07342

Rethinking ASTE: A Minimalist Tagging Scheme Alongside Contrastive Learning
Aspect Sentiment Triplet Extraction (ASTE) is a burgeoning subtask of fine-grained sentiment analysis, aiming to extract structured sentiment triplets from unstructured textual data. Existing approaches to ASTE often complicate the task with additional structures or external data. In this research, we propose a novel tagging scheme and employ a contrastive learning approach to mitigate these challenges. The proposed approach demonstrates comparable or superior performance in comparison to state…

Multi-task Manipulation Policy Modeling with Visuomotor Latent Diffusion
Wenhui Tan, Bei Liu, Junbo Zhang, Ruihua Song, Jianlong Fu
https://arxiv.org/abs/2403.07312

Multi-task Manipulation Policy Modeling with Visuomotor Latent Diffusion
Modeling a generalized visuomotor policy has been a longstanding challenge for both computer vision and robotics communities. Existing approaches often fail to efficiently leverage cross-dataset resources or rely on heavy Vision-Language models, which require substantial computational resources, thereby limiting their multi-task performance and application potential. In this paper, we introduce a novel paradigm that effectively utilizes latent modeling of manipulation skills and an efficient vi…

Rethinking ASTE: A Minimalist Tagging Scheme Alongside Contrastive Learning
Qiao Sun, Liujia Yang, Minghao Ma, Nanyang Ye, Qinying Gu
https://arxiv.org/abs/2403.07342

Rethinking ASTE: A Minimalist Tagging Scheme Alongside Contrastive Learning
Aspect Sentiment Triplet Extraction (ASTE) is a burgeoning subtask of fine-grained sentiment analysis, aiming to extract structured sentiment triplets from unstructured textual data. Existing approaches to ASTE often complicate the task with additional structures or external data. In this research, we propose a novel tagging scheme and employ a contrastive learning approach to mitigate these challenges. The proposed approach demonstrates comparable or superior performance in comparison to state…

This https://arxiv.org/abs/2402.15281 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Neural Implicit Swept Volume Models for Fast Collision Detection
Collision detection is one of the most time-consuming operations during motion planning. Thus, there is an increasing interest in exploring machine learning techniques to speed up collision detection and sampling-based motion planning. A recent line of research focuses on utilizing neural signed distance functions of either the robot geometry or the swept volume of the robot motion. Building on this, we present a novel neural implicit swept volume model to continuously represent arbitrary motio…

This https://arxiv.org/abs/2403.06935 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Naming, Describing, and Quantifying Visual Objects in Humans and LLMs
While human speakers use a variety of different expressions when describing the same object in an image, giving rise to a distribution of plausible labels driven by pragmatic constraints, the extent to which current Vision \& Language Large Language Models (VLLMs) can mimic this crucial feature of language use is an open question. This applies to common, everyday objects, but it is particularly interesting for uncommon or novel objects for which a category label may be lacking or fuzzy. Further…

This https://arxiv.org/abs/2403.02604 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

UniDoorManip: Learning Universal Door Manipulation Policy Over Large-scale and Diverse Door Manipulation Environments
Learning a universal manipulation policy encompassing doors with diverse categories, geometries and mechanisms, is crucial for future embodied agents to effectively work in complex and broad real-world scenarios. Due to the limited datasets and unrealistic simulation environments, previous works fail to achieve good performance across various doors. In this work, we build a novel door manipulation environment reflecting different realistic door manipulation mechanisms, and further equip this en…

This https://arxiv.org/abs/2403.06935 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Naming, Describing, and Quantifying Visual Objects in Humans and LLMs
While human speakers use a variety of different expressions when describing the same object in an image, giving rise to a distribution of plausible labels driven by pragmatic constraints, the extent to which current Vision \& Language Large Language Models (VLLMs) can mimic this crucial feature of language use is an open question. This applies to common, everyday objects, but it is particularly interesting for uncommon or novel objects for which a category label may be lacking or fuzzy. Further…

Language-Grounded Dynamic Scene Graphs for Interactive Object Search with Mobile Manipulation
Daniel Honerkamp, Martin Buchner, Fabien Despinoy, Tim Welschehold, Abhinav Valada
https://arxiv.org/abs/2403.08605

Language-Grounded Dynamic Scene Graphs for Interactive Object Search with Mobile Manipulation
To fully leverage the capabilities of mobile manipulation robots, it is imperative that they are able to autonomously execute long-horizon tasks in large unexplored environments. While large language models (LLMs) have shown emergent reasoning skills on arbitrary tasks, existing work primarily concentrates on explored environments, typically focusing on either navigation or manipulation tasks in isolation. In this work, we propose MoMa-LLM, a novel approach that grounds language models within s…

The Missing Piece in Model Editing: A Deep Dive into the Hidden Damage Brought By Model Editing
Jianchen Wang, Zhouhong Gu, Zhuozhi Xiong, Hongwei Feng, Yanghua Xiao
https://arxiv.org/abs/2403.07825

The Missing Piece in Model Editing: A Deep Dive into the Hidden Damage Brought By Model Editing
Large Language Models have revolutionized numerous tasks with their remarkable efficacy.However, the editing of these models, crucial for rectifying outdated or erroneous information, often leads to a complex issue known as the ripple effect in the hidden space. This effect, while difficult to detect, can significantly impede the efficacy of model editing tasks and deteriorate model performance.This paper addresses this scientific challenge by proposing a novel evaluation methodology, Graphical…

DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation
Chen Wang, Haochen Shi, Weizhuo Wang, Ruohan Zhang, Li Fei-Fei, C. Karen Liu
https://arxiv.org/abs/2403.07788

DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation
Imitation learning from human hand motion data presents a promising avenue for imbuing robots with human-like dexterity in real-world manipulation tasks. Despite this potential, substantial challenges persist, particularly with the portability of existing hand motion capture (mocap) systems and the difficulty of translating mocap data into effective control policies. To tackle these issues, we introduce DexCap, a portable hand motion capture system, alongside DexIL, a novel imitation algorithm …

The Missing Piece in Model Editing: A Deep Dive into the Hidden Damage Brought By Model Editing
Jianchen Wang, Zhouhong Gu, Zhuozhi Xiong, Hongwei Feng, Yanghua Xiao
https://arxiv.org/abs/2403.07825

The Missing Piece in Model Editing: A Deep Dive into the Hidden Damage Brought By Model Editing
Large Language Models have revolutionized numerous tasks with their remarkable efficacy.However, the editing of these models, crucial for rectifying outdated or erroneous information, often leads to a complex issue known as the ripple effect in the hidden space. This effect, while difficult to detect, can significantly impede the efficacy of model editing tasks and deteriorate model performance.This paper addresses this scientific challenge by proposing a novel evaluation methodology, Graphical…