Tootfinder

Someone said “Everything you know about Cinco de Mayo is wrong” but all I know is that it’s the 5th of May but damn even that is incorrect I guess!

@… thanks for the boost, friend. Unfortunately, I don't think it will be of much use. The person speaks in broken English and is spreading incorrect or just straight useless information. This REALLY sucks that folks like you and I do so much on there to keep people knowledgeable and somebody just squanders an opportunity like that to do such a good thing!😩

@… As someone who is currently appealing an incorrect bill because they’re charging me as out-of-network for a provider that is clearly listed as in-network in their own documents… yeah.

This https://arxiv.org/abs/2404.02124 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models
Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable format in assessments and practices. One of the most important aspects of MCQs is the distractors, i.e., incorrect options that are designed to target common errors or misconceptions among real students. To date, the task of crafting high-quality distractors largely remains a labor and time-intensive process for teachers and learning content designers, w…

#Rant. There are mansplainers and there are mansplainers who mansplain to me confidently, in writing, the *definitions* of the topics of my expertise. Their definitions are incorrect or shaky and they don't cite their sources or provide a basis. #Mansplaining Ultra Pro Max.
Why do men wa…

Another day, another person barely caught the train on #Poznań Główny station, because of the useless platform numbers and confusing markings.
The "new" train station features two adjacent doors, leading to the same staircase. Above one of them, the label says "platform 3". Above the other, it says "platform 4". How this can be anything but confusing? The most logical (and incorrect) conclusion is that one track belongs to platform 3, while the other to platform 4.
#rail

This https://arxiv.org/abs/2309.04909 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Bicoptor 2.0: Addressing Challenges in Probabilistic Truncation for Enhanced Privacy-Preserving Machine Learning
This paper primarily focuses on analyzing the problems and proposing solutions for the probabilistic truncation protocol in existing PPML works from the perspectives of accuracy and efficiency. In terms of accuracy, we reveal that precision selections recommended in some of the existing works are incorrect. We conduct a thorough analysis of their open-source code and find that their errors were mainly due to simplified implementation, more specifically, fixed numbers are used instead of random …

Determining the difference between local acceleration and local gravity: applications of the equivalence principle to relativistic trajectories
Steven A. Balbus
https://arxiv.org/abs/2403.03965

Determining the difference between local acceleration and local gravity: applications of the equivalence principle to relativistic trajectories
We show by direct calculation that the common Equivalence Principle explanation for why gravity must deflect light is quantitatively incorrect by a factor of three in Schwarzschild geometry. It is therefore possible, at least as a matter of principle, to tell the difference between local acceleration and a true gravitational field by measuring the local deflection of light. We calculate as well the deflection of test particles of arbitrary energy, and construct a leading-order coordinate transf…

Optimal Denial-of-Service Attacks Against Status Updating
Saad Kriouile, Mohamad Assaad, Deniz G\"und\"uz, Touraj Soleymani
https://arxiv.org/abs/2403.04489

Optimal Denial-of-Service Attacks Against Status Updating
In this paper, we investigate denial-of-service attacks against status updating. The target system is modeled by a Markov chain and an unreliable wireless channel, and the performance of status updating in the target system is measured based on two metrics: age of information and age of incorrect information. Our objective is to devise optimal attack policies that strike a balance between the deterioration of the system's performance and the adversary's energy. We model the optimal problem as a…

Modification to the Jeans criterion by external tides: Anisotropic fragmentation and formation of filaments
Guang-Xing Li
https://arxiv.org/abs/2403.02612 https://arxiv.org/pdf/2403.02612
arXiv:2403.02612v1 Announce Type: new
Abstract: The Jeans criterion sets the foundation of our understanding of gravitational collapse. Jog studied the fragmentation of gas under external tides and derived a dispersion relation $$
l' = l_{\rm Jeans} \frac{1} {(1 \lambda_0' / 4 \pi G \rho_0)^{1/2}} \;. $$ She further concludes that the Jeans mass is $m_{\rm incorrect}'=m_{\rm Jeans} ( 1/(1 \lambda_0' / 4 \pi G \rho_0)^{3/2})$. We clarify that due to the inhomogeneous nature of tides, this characteristic mass is incorrect. Under weak tides, the mass is $m \approx \rho\, l_1 l_2 l_3$, where the modifications to Jeans lengths along all three dimensions need to be considered; when the tide is strong enough, collapse can only occur once 1 or 2 dimensions. In the latter case, tides can stretch the gas, leading to the formation of filaments.

🔊 #NowPlaying on KEXP's #DriveTime
Ibibio Sound Machine:
🎵 Political Incorrect
#IbibioSoundMachine #newRelease 🆕 album
#Bandcamp

OMG my long time online friend @… has just made a contribution to Gaiman/Pratchett canon on the FIRST PAGE of GOOD OMENS
Neil Gaiman on Tumblr: (first off: I'm not an astronomer, and I may be wildly off, but…) I had always assumed that "This too was incorrect. By almost a...

SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation
Chi Zhang, Qilong Han, Rui Chen, Xiangyu Zhao, Peng Tang, Hongtao Song
https://arxiv.org/abs/2403.04278

SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation
Traditional sequential recommendation methods assume that users' sequence data is clean enough to learn accurate sequence representations to reflect user preferences. In practice, users' sequences inevitably contain noise (e.g., accidental interactions), leading to incorrect reflections of user preferences. Consequently, some pioneer studies have explored modeling sequentiality and correlations in sequences to implicitly or explicitly reduce noise's influence. However, relying on only available…

This https://arxiv.org/abs/2405.01461 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

SATO: Stable Text-to-Motion Framework
Is the Text to Motion model robust? Recent advancements in Text to Motion models primarily stem from more accurate predictions of specific actions. However, the text modality typically relies solely on pre-trained Contrastive Language-Image Pretraining (CLIP) models. Our research has uncovered a significant issue with the text-to-motion model: its predictions often exhibit inconsistent outputs, resulting in vastly different or even incorrect poses when presented with semantically similar or ide…

CodeFort: Robust Training for Code Generation Models
Yuhao Zhang, Shiqi Wang, Haifeng Qian, Zijian Wang, Mingyue Shang, Linbo Liu, Sanjay Krishna Gouda, Baishakhi Ray, Murali Krishna Ramanathan, Xiaofei Ma, Anoop Deoras
https://arxiv.org/abs/2405.01567

CodeFort: Robust Training for Code Generation Models
Code generation models are not robust to small perturbations, which often lead to inconsistent and incorrect generations and significantly degrade the performance of these models. Improving the robustness of code generation models is crucial to better user experience when these models are deployed in real-world applications. However, existing efforts have not addressed this issue for code generation models. To fill this gap, we propose CodeFort, a framework to improve the robustness of code gen…

We are at a stage in human history where huge trust is placed in statistical machines, that are unpredictable and easily manipulated, for important business – and personal – decisions.

Blown away when people respond to screenshots of failed responses with screenshots of successful responses, as if the tool has "learned" the correct response.

As if it can't just as easily provide an incorrect response again.

It's unsettling to me that people don't…

So, it turns out, ASP.NET Core applications without Open Telemetry still send a traceparent header, with the tracing flag off. It also turns out that an ASP.NET Core application that does use OTEL will not send traces if they receive a traceparent header with the tracing flag off. And it also turns out, that the documentation on how to change this behaviour, by using the OTEL_TRACES_SAMPLER environment variable, is incorrect. This variable is not used yet. Fun.

Can Small Language Models be Good Reasoners for Sequential Recommendation?
Yuling Wang, Changxin Tian, Binbin Hu, Yanhua Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Liang Pang, Xiao Wang
https://arxiv.org/abs/2403.04260

Can Small Language Models be Good Reasoners for Sequential Recommendation?
Large language models (LLMs) open up new horizons for sequential recommendations, owing to their remarkable language comprehension and generation capabilities. However, there are still numerous challenges that should be addressed to successfully implement sequential recommendations empowered by LLMs. Firstly, user behavior patterns are often complex, and relying solely on one-step reasoning from LLMs may lead to incorrect or task-irrelevant responses. Secondly, the prohibitively resource requir…

Non-profit noyb files a GDPR complaint against OpenAI in Austria on behalf of an unnamed public figure, who found ChatGPT produced his incorrect birth date (Natasha Lomas/TechCrunch)
https://techcrunch.com/2024/04/28/chatgpt-gdpr-complaint-noyb/

ChatGPT's 'hallucination' problem hit with another privacy complaint in EU | TechCrunch
OpenAI is facing another privacy complaint in the European Union. This one, which has been filed by privacy rights nonprofit noyb on behalf of an OpenAI is facing another privacy complaint in the European Union that targets the inability of its AI chatbot ChatGPT to correct misinformation it generates about individuals.

@…
Lisa, at your discretion:
@… has been live-tweeting #Trump trial, in a very newbie-friendly, easy to understand way, especially if …

How Can I Get It Right? Using GPT to Rephrase Incorrect Trainee Responses
Jionghao Lin, Zifei Han, Danielle R. Thomas, Ashish Gurung, Shivang Gupta, Vincent Aleven, Kenneth R. Koedinger
https://arxiv.org/abs/2405.00970

How Can I Get It Right? Using GPT to Rephrase Incorrect Trainee Responses
One-on-one tutoring is widely acknowledged as an effective instructional method, conditioned on qualified tutors. However, the high demand for qualified tutors remains a challenge, often necessitating the training of novice tutors (i.e., trainees) to ensure effective tutoring. Research suggests that providing timely explanatory feedback can facilitate the training process for trainees. However, it presents challenges due to the time-consuming nature of assessing trainee performance by human exp…

Is it incorrect to want to play Sheryl Crow's song 'Soak up the sun' on April 8th

An efficient quantifier elimination procedure for Presburger arithmetic
Christoph Haase, Shankara Narayanan Krishna, Khushraj Madnani, Om Swostik Mishra, Georg Zetzsche
https://arxiv.org/abs/2405.01183

An efficient quantifier elimination procedure for Presburger arithmetic
All known quantifier elimination procedures for Presburger arithmetic require doubly exponential time for eliminating a single block of existentially quantified variables. It has even been claimed in the literature that this upper bound is tight. We observe that this claim is incorrect and develop, as the main result of this paper, a quantifier elimination procedure eliminating a block of existentially quantified variables in singly exponential time. As corollaries, we can establish the precise…

WitheredLeaf: Finding Entity-Inconsistency Bugs with LLMs
Hongbo Chen, Yifan Zhang, Xing Han, Huanyao Rong, Yuheng Zhang, Tianhao Mao, Hang Zhang, XiaoFeng Wang, Luyi Xing, Xun Chen
https://arxiv.org/abs/2405.01668

WitheredLeaf: Finding Entity-Inconsistency Bugs with LLMs
Originating from semantic bugs, Entity-Inconsistency Bugs (EIBs) involve misuse of syntactically valid yet incorrect program entities, such as variable identifiers and function names, which often have security implications. Unlike straightforward syntactic vulnerabilities, EIBs are subtle and can remain undetected for years. Traditional detection methods, such as static analysis and dynamic testing, often fall short due to the versatile and context-dependent nature of EIBs. However, with advanc…

The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?
Alex Gu, Wen-Ding Li, Naman Jain, Theo X. Olausson, Celine Lee, Koushik Sen, Armando Solar-Lezama
https://arxiv.org/abs/2402.19475

The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?
While language models are increasingly more proficient at code generation, they still frequently generate incorrect programs. Many of these programs are obviously wrong, but others are more subtle and pass weaker correctness checks such as being able to compile. In this work, we focus on these counterfeit samples: programs sampled from a language model that 1) have a high enough log-probability to be generated at a moderate temperature and 2) pass weak correctness checks. Overall, we discover t…

This https://arxiv.org/abs/2402.02612 has been replaced.
link: https://scholar.google.com/scholar?q=a

Fast Explicit-Input Assistance for Teleoperation in Clutter
The performance of prediction-based assistance for robot teleoperation degrades in unseen or goal-rich environments due to incorrect or quickly-changing intent inferences. Poor predictions can confuse operators or cause them to change their control input to implicitly signal their goal. We present a new assistance interface for robotic manipulation where an operator can explicitly communicate a manipulation goal by pointing the end-effector. The pointing target specifies a region for local pose…

So I noticed that some bots(?) have been adding foreign language info to my Wikidata entry. Neat!
Except that some of these seem to be incorrect. Most of the non-English ones list "researcher" (which, sure I guess?), but both the Mongolia and Dutch are translated by Google Translate as "scientist."
Anyone know what's up with this? Mistranslation? Error? Is Google Translate wrong? Is this showing up in anyone else's Wikidata pages?
Mongolian: эрд…

How refreshing to see someone actually get the story of Germany's nuclear phase-out right, instead of relying on the same old incorrect tribal tropes!
Why Germany ditched nuclear before coal – and why it won’t go back https://theconversation.com/why-german…

Why Germany ditched nuclear before coal – and why it won’t go back
Understanding Berlin’s nuclear exit, one year on.

A new form of scam? Our website gets a manageable amount of spam submissions to our contact form. What’s new (to me) is that some of them claim to be individuals requesting refunds for incorrect charges by us. Which is impossible since we have no e-commerce. A spate of these came in about a month ago. Just an interesting pattern. Also, reCAPCHA isn’t blocking them.

Interesting, some empirical research on how GPT4 /ChatGPT performs in summarizing. Still the low rate of errors can be unacceptable in some contexts. As noted "Life-critical medical decisions should remain based on full, critical, and thoughtful evaluation of the full text of research articles in context with clinical guidelines.".
http…

Quality, Accuracy, and Bias in ChatGPT-Based Summarization of Medical Abstracts
PURPOSE Worldwide clinical knowledge is expanding rapidly, but physicians have sparse time to review scientific literature. Large language models (eg, Chat Generative Pretrained Transformer [ChatGPT]), might help summarize and prioritize research articles to review. However, large language models sometimes “hallucinate” incorrect information. METHODS We evaluated ChatGPT’s ability to summarize 140 peer-reviewed abstracts from 14 journals. Physicians rated the quality, accuracy, and bias …

Curiosity-driven Red-teaming for Large Language Models
Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang, Aldo Pareja, James Glass, Akash Srivastava, Pulkit Agrawal
https://arxiv.org/abs/2402.19464

Curiosity-driven Red-teaming for Large Language Models
Large language models (LLMs) hold great potential for many natural language applications but risk generating incorrect or toxic content. To probe when an LLM generates unwanted content, the current paradigm is to recruit a \textit{red team} of human testers to design input prompts (i.e., test cases) that elicit undesirable responses from LLMs. However, relying solely on human testers is expensive and time-consuming. Recent works automate red teaming by training a separate red team LLM with rein…

This https://arxiv.org/abs/2403.01548 has been replaced.
link: https://scholar.google.com/scholar?q=a

In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation
Large language models (LLMs) frequently hallucinate and produce factual errors, yet our understanding of why they make these errors remains limited. In this study, we delve into the underlying mechanisms of LLM hallucinations from the perspective of inner representations, and discover a salient pattern associated with hallucinations: correct generations tend to have sharper context activations in the hidden states of the in-context tokens, compared to the incorrect ones. Leveraging this insight…

Anarchy in the APSP: Algorithm and Hardness for Incorrect Implementation of Floyd-Warshall
Jaehyun Koo
https://arxiv.org/abs/2404.08173 https://

Anarchy in the APSP: Algorithm and Hardness for Incorrect Implementation of Floyd-Warshall
The celebrated Floyd-Warshall algorithm efficiently computes the all-pairs shortest path, and its simplicity made it a staple in computer science classes. Frequently, students discover a variant of this Floyd-Warshall algorithm by mixing up the loop order, ending up with the incorrect APSP matrix. This paper considers a computational problem of computing this incorrect APSP matrix. We will propose efficient algorithms for this problem and prove that this incorrect variant is APSP-complete.

"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust
Sunnie S. Y. Kim, Q. Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, Jennifer Wortman Vaughan
https://arxiv.org/abs/2405.00623

"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust
Widely deployed large language models (LLMs) can produce convincing yet incorrect outputs, potentially misleading users who may rely on them as if they were correct. To reduce such overreliance, there have been calls for LLMs to communicate their uncertainty to end users. However, there has been little empirical work examining how users perceive and act upon LLMs' expressions of uncertainty. We explore this question through a large-scale, pre-registered, human-subject experiment (N=404) in whic…

Happy π day!
To celebrate, let's look back at this 127-year-old bill that was passed in the Indiana House of Representatives which attempted to legislate a wildly incorrect solution to the squaring a circle problem and thereby legalize an incorrect value of π.
https://en.wikipedia.org/wiki/Indiana_

Indiana pi bill - Wikipedia

PVF (Parameter Vulnerability Factor): A Quantitative Metric Measuring AI Vulnerability and Resilience Against Parameter Corruptions
Xun Jiao, Fred Lin, Harish D. Dixit, Joel Coburn, Abhinav Pandey, Han Wang, Jianyu Huang, Venkat Ramesh, Wang Xu, Daniel Moore, Sriram Sankar
https://arxiv.org/abs/2405.01741

PVF (Parameter Vulnerability Factor): A Quantitative Metric Measuring AI Vulnerability and Resilience Against Parameter Corruptions
Reliability of AI systems is a fundamental concern for the successful deployment and widespread adoption of AI technologies. Unfortunately, the escalating complexity and heterogeneity of AI hardware systems make them inevitably and increasingly susceptible to hardware faults (e.g., bit flips) that can potentially corrupt model parameters. Given this challenge, this paper aims to answer a critical question: How likely is a parameter corruption to result in an incorrect model output? To systemati…

This https://arxiv.org/abs/2301.11751 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Manifolds with trivial Chern classes II: Manifolds Isogenous to a Torus Product, coframed Manifolds and a question by Baldassarri
Motivated by a general question addressed by Mario Baldassarri in 1956, we discuss characterizations of the Pseudo-Abelian Varieties introduced by Roth, and we introduce a first new notion, of Manifolds Isogenous to a k-Torus Product: the latter have the last k Chern classes trivial in rational cohomology and vanishing Chern numbers. We show that in dimension 2 the latter class is the correct substitute for some incorrect assertions by Enriques, Dantoni, Roth and Baldassarri: these are the surf…

Constrained Decoding for Code Language Models via Efficient Left and Right Quotienting of Context-Sensitive Grammars
Daniel Melcer, Nathan Fulton, Sanjay Krishna Gouda, Haifeng Qian
https://arxiv.org/abs/2402.17988

Constrained Decoding for Code Language Models via Efficient Left and Right Quotienting of Context-Sensitive Grammars
Large Language Models are powerful tools for program synthesis and advanced auto-completion, but come with no guarantee that their output code is syntactically correct. This paper contributes an incremental parser that allows early rejection of syntactically incorrect code, as well as efficient detection of complete programs for fill-in-the-middle (FItM) tasks. We develop Earley-style parsers that operate over left and right quotients of arbitrary context-free grammars, and we extend our increm…

This https://arxiv.org/abs/2404.01276 has been replaced.
link: https://scholar.google.com/scholar?q=a

Variable-Length Stop-Feedback Coding for Minimum Age of Incorrect Information
The Age of Incorrect Information (AoII) is examined within the context of remote monitoring of a Markov source using variable-length stop-feedback (VLSF) coding. Leveraging recent results on the non-asymptotic channel coding rate, we consider sources with small cardinality, where feedback is non-instantaneous as the transmitted information and feedback message have comparable lengths. We focus on the feedback sequence, i.e. the times of feedback transmissions, and derive AoII-optimal and delay-…

No, really. LLMs are absolutely not fancy autocomplete. Really.
> In this case, the bug was in the step where the model chooses these numbers. Akin to being lost in translation, the model chose slightly wrong numbers, which produced word sequences that made no sense. More technically, inference kernels produced incorrect results when used in certain GPU configurations.

LCPS data van gisteren en vandaag is er nu wel, maar deze is incorrect/incompleet, dus voorlopig geen update.
Wat wel lijkt te kloppen: gisteren en vandaag 19 nieuwe opnames, dat is meer dan de vergelijkbare dagen vorige week.
#qp2t

This https://arxiv.org/abs/2402.00081 has been replaced.
link: https://scholar.google.com/scholar?q=a

Comment on "The Tully-Fisher law and dark matter effects derived via modified symmetries" by Arraut Ivan
It has been claimed in I. Arraut, 2023 EPL 144 29003 [arXiv:2311.05652] that General Relativity can generate effects equivalent to dark matter, based on a "new modified symmetry that emerges at galactic scale". We show that (i) the spacetime considered is unphysical, violating energy conditions everywhere; (ii) actually no new symmetry emerges, which results from incorrect definitions of angular momentum, velocity, and arclength in the proposed geometry; (iii) no Tully-Fisher law, or flat rotat…

It's quite annoying to see a new amazing tool be released and the vast majority using it in the most incorrect way possible, then going "tool is dumb, don't work, broken"....
Well, if you'd start using it in a way that actually makes fucking sense then it wouldn't be "dumb" because it can do the things it's meant to do, fairly well...

This https://arxiv.org/abs/2402.02612 has been replaced.
link: https://scholar.google.com/scholar?q=a

Fast Explicit-Input Assistance for Teleoperation in Clutter
The performance of prediction-based assistance for robot teleoperation degrades in unseen or goal-rich environments due to incorrect or quickly-changing intent inferences. Poor predictions can confuse operators or cause them to change their control input to implicitly signal their goal. We present a new assistance interface for robotic manipulation where an operator can explicitly communicate a manipulation goal by pointing the end-effector. The pointing target specifies a region for local pose…

AT&T believes the February 22 outage was "caused by the application and execution of an incorrect process" as it was expanding its network, "not a cyber attack" (ABC News)
https://abcnews.go.com/US/att-outage-impacting…

AT&T outage caused by software update, company says
AT&T says they have "restored wireless service to all our affected customers."

Former Raiders CB Damon Arnette disputes methamphetamine arrest, claims he has prescription https://www.yardbarker.com/nfl/articles/former_raiders_cb_damon_arnette_disputes_methamphetami…

Former Raiders CB Damon Arnette disputes methamphetamine arrest, claims he has prescription
The attorneys for former NFL cornerback Damon Arnette publicly disputed the Monday report from Ian Rapoport of NFL Network in which Rapoport said that Arnette was arrested and charged with possession of less than a gram of meth and unlawful carrying of a firearm on Jan. 6 at 3:30 a.m. in Richardson, Texas. Arnette’s attorneys, Jason Lampert and Thomas Wynne, called the report “simply incorrect.” “Our client, at the time of the stop, was unable to provide law enforcement with his presc…

⛳ @… #Golf
Whoops!
Via PGA TOUR Communications @PGATOURComms
·
5m
Jordan Spieth has been disqualified from The Genesis Invitational for signing for an incorrect scorecard.
Spieth signed for a 3 and made a 4 on No. 4.

Hey hey all my #Krita artists, does anyone else who uses a Wacom notice the app being too sensitive when using the freehand selection / lasso tool?
It often seems to release the selection before I actually lift my pen off the tablet resulting in an incorrect selection. This is annoying for obvious reasons. Any way to fix this?

You know how some foods are labelled “no lactose” or “sugar free” — we need something similar for software services not using LLMs to provide (confabulated and often incorrect) answers to questions.

Revealed: the secret algorithm that controls the lives of Serco’s immigration detainees, The Guardian
'Imagine there’s a secret rating that dictates where you sleep and whether you are forced to wear handcuffs to a doctor’s appointment. And imagine that rating is based on incorrect information or unfair assumptions about the type of person you are.'

This https://arxiv.org/abs/2402.00081 has been replaced.
link: https://scholar.google.com/scholar?q=a

Comment on "The Tully-Fisher law and dark matter effects derived via modified symmetries" by Arraut Ivan
It has been claimed in I. Arraut, 2023 EPL 144 29003 [arXiv:2311.05652] that General Relativity can generate effects equivalent to dark matter, based on a "new modified symmetry that emerges at galactic scale". We show that (i) the spacetime considered is unphysical, violating energy conditions everywhere; (ii) actually no new symmetry emerges, which results from incorrect definitions of angular momentum, velocity, and arclength in the proposed geometry; (iii) no Tully-Fisher law, or flat rotat…

Time check after DST
If your timezone is incorrect now, please let me know. Thanks.
It was, 9PM EST, (6PM PT / 2AM GMT / 3AM CET / 1PM AEDT / 2PM NZST)
@…

They’ll actually get more money on the finalized deal.
“MAC commissioner Jon Steinbrecher, who is one of the 11-member CFP Management Committee members, sent a memo to his league administrators saying that such reports (as The Athletic’s) are "incorrect" and premature.”

GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion
Xueyi Liu, Li Yi
https://arxiv.org/abs/2402.14810 https:/…

GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion
In this work, we tackle the challenging problem of denoising hand-object interactions (HOI). Given an erroneous interaction sequence, the objective is to refine the incorrect hand trajectory to remove interaction artifacts for a perceptually realistic sequence. This challenge involves intricate interaction noise, including unnatural hand poses and incorrect hand-object relations, alongside the necessity for robust generalization to new interactions and diverse noise patterns. We tackle those ch…

This https://arxiv.org/abs/1902.09608 has been replaced.
link: https://scholar.google.com/scholar?q=a

On Binscatter
Binscatter is a popular method for visualizing bivariate relationships and conducting informal specification testing. We study the properties of this method formally and develop enhanced visualization and econometric binscatter tools. These include estimating conditional means with optimal binning and quantifying uncertainty. We also highlight a methodological problem related to covariate adjustment that can yield incorrect conclusions. We revisit two applications using our methodology and find…

Optimizing Portfolio Management and Risk Assessment in Digital Assets Using Deep Learning for Predictive Analysis
Qishuo Cheng, Le Yang, Jiajian Zheng, Miao Tian, Duan Xin
https://arxiv.org/abs/2402.15994 https://arxiv.org/pdf/2402.15994
arXiv:2402.15994v1 Announce Type: new
Abstract: Portfolio management issues have been extensively studied in the field of artificial intelligence in recent years, but existing deep learning-based quantitative trading methods have some areas where they could be improved. First of all, the prediction mode of stocks is singular; often, only one trading expert is trained by a model, and the trading decision is solely based on the prediction results of the model. Secondly, the data source used by the model is relatively simple, and only considers the data of the stock itself, ignoring the impact of the whole market risk on the stock. In this paper, the DQN algorithm is introduced into asset management portfolios in a novel and straightforward way, and the performance greatly exceeds the benchmark, which fully proves the effectiveness of the DRL algorithm in portfolio management. This also inspires us to consider the complexity of financial problems, and the use of algorithms should be fully combined with the problems to adapt. Finally, in this paper, the strategy is implemented by selecting the assets and actions with the largest Q value. Since different assets are trained separately as environments, there may be a phenomenon of Q value drift among different assets (different assets have different Q value distribution areas), which may easily lead to incorrect asset selection. Consider adding constraints so that the Q values of different assets share a Q value distribution to improve results.

I've published a detailed article about #ChatGPT hallucination minimization using predefined #SPARQL-based query templates scoped to Linked Open Data (LOD) Cloud Knowledge Graphs such as #UniProtKB…

Reducing Hallucinations in ChatGPT using Predefined Query Templates scoped to Knowledge Graphs
In the fast-paced world of artificial intelligence, chatbots using language model strategies are becoming more common. However, these chatbots sometimes generate responses based on incorrect or fabricated information, a problem often referred to as “hallucinations.

Validating a lutetium frequency reference
Kyle J. Arnold, Scott Bustabad, Qin Qichen, Zhao Zhang, Qi Zhao, Murray D. Barrett
https://arxiv.org/abs/2404.16414 https://arxiv.org/pdf/2404.16414
arXiv:2404.16414v1 Announce Type: new
Abstract: We review our progress in developing a frequency reference with singly ionized lutetium and give estimates of the levels of inaccuracy we expect to achieve in the near future with both the $^1S_0\leftrightarrow{}^3D_1$ and $^1S_0\leftrightarrow{}^3D_2$ transitions. Based on established experimental results, we show that inaccuracies at the low $10^{-19}$ level are readily achievable for the $^1S_0\leftrightarrow{}^3D_1$ transition, and the frequency ratio between the two transitions is limited almost entirely by the BBR shift. We argue that the frequency ratio measured within the one apparatus provides a well-defined metric to compare and establish the performance of remotely located systems. For the measurement of an in situ frequency ratio, relativistic shifts drop out and both transitions experience the same electromagnetic environment. Consequently, the uncertainty budget for the ratio is practically identical to the uncertainty budgets for the individual transitions. If the ratios for two or more systems disagree we can be certain at least one of the clock assessments is incorrect. If they agree, subsequent comparisons on one transition would only differ by relativistic effects. Since motional effects are easily assessed and typically small for a heavy ion, only the differential gravitational red-shift will significantly contribute and this can be confirmed by comparison on the second transition.

Human-in-the-Loop Synthetic Text Data Inspection with Provenance Tracking
Hong Jin Kang, Fabrice Harel-Canada, Muhammad Ali Gulzar, Violet Peng, Miryung Kim
https://arxiv.org/abs/2404.18881

Human-in-the-Loop Synthetic Text Data Inspection with Provenance Tracking
Data augmentation techniques apply transformations to existing texts to generate additional data. The transformations may produce low-quality texts, where the meaning of the text is changed and the text may even be mangled beyond human comprehension. Analyzing the synthetically generated texts and their corresponding labels is slow and demanding. To winnow out texts with incorrect labels, we develop INSPECTOR, a human-in-the-loop data inspection technique. INSPECTOR combines the strengths of pr…

Kinetic theory of vacuum pair production in uniform electric fields revisited
I. A. Aleksandrov, A. Kudlis, A. I. Klochai
https://arxiv.org/abs/2403.17204 …

Kinetic theory of vacuum pair production in uniform electric fields revisited
We investigate the phenomenon of electron-positron pair production from vacuum in the presence of a uniform time-dependent electric field of arbitrary polarization. Taking into account the interaction with the external classical background in a nonperturbative manner, we quantize the electron-positron field and derive a system of ten quantum kinetic equations (QKEs) showing that the previously-used QKEs are incorrect once the external field rotates in space. We employ then the Wigner-function f…

This https://arxiv.org/abs/2307.13696 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The Dark Energy Survey Supernova Program: Cosmological Biases from Host Galaxy Mismatch of Type Ia Supernovae
Redshift measurements, primarily obtained from host galaxies, are essential for inferring cosmological parameters from type Ia supernovae (SNe Ia). Matching SNe to host galaxies using images is non-trivial, resulting in a subset of SNe with mismatched hosts and thus incorrect redshifts. We evaluate the host galaxy mismatch rate and resulting biases on cosmological parameters from simulations modeled after the Dark Energy Survey 5-Year (DES-SN5YR) photometric sample. For both DES-SN5YR data and …

The number of times someone calls me by the obvious incorrect spelling of my last name is significant enough to mention; almost as many as call me by my father's [different] first name, despite most not even knowing him.

This https://arxiv.org/abs/2312.07159 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Rate-Splitting Multiple Access for Semantic-Aware Networks: an Age of Incorrect Information Perspective
In this letter, we design a downlink multi-user communication framework based on Rate-Splitting Multiple Access (RSMA) for semantic-aware networks. First, we formulate an optimization problem to obtain the optimal user scheduling, precoding, and power allocation schemes jointly. We consider the metric Age of Incorrect Information (AoII) in the objective function of the formulated problem to maximize the freshness of the overall information to be transmitted. Using big-M and Successive Convex Ap…

Time-dependent Stellar Flare Models of Deep Atmospheric Heating
Adam F. Kowalski (University of Colorado, National Solar Observatory, Laboratory for Atmospheric and Space Physics), Joel C. Allred (NASA Goddard Space Flight Center), Mats Carlsson (Institute of Theoretical Astrophysics, University of Oslo, Rosseland Centre for Solar Physics, University of Oslo)

Time-dependent Stellar Flare Models of Deep Atmospheric Heating
Optical flares have been observed from magnetically active stars for many decades; unsurprisingly, the spectra and temporal evolution are complicated. For example, the shortcomings of optically thin, static slab models have long been recognized when confronted with the observations. A less incorrect -- but equally simple -- phenomenological $T \approx 9000$ K blackbody model has instead been widely adopted in the absence of realistic (i.e., observationally-tested) time-dependent, atmospheric mo…

The Reddit user is skeptical about BitSight, considering it ineffective without providing details, and invites others to correct their assumption if incorrect. https://reddit.com/r/cybersecurity/comments/1bzaedv/

#Wordle 968 4/6*
⬜⬜🟨⬜⬜ <1% of 259,020 (209)
🟨🟨⬜🟨🟨 <1% of 904 (1)
🟩🟩🟩🟩⬜ 1% of 180 (1)
🟩🟩🟩🟩🟩
WordleBot
Skill 50/99
Luck 63/99
When I watched the letters turning green I was really thinking I got it, and then boom! no I did not. It made me really laugh as I looked to see what other word it could be!
Well huh, so dumb, that incorrect letter was one I had eliminated on my 1st guess!

This https://arxiv.org/abs/2402.17814 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Comment on "Source of black bounces in Rastall gravity''
In Atazadeh and Hadi (JCAP \textbf{01}, 067 (2024)), the authors proposed that black bounce solutions, such as the Simpson-Visser and the Bardeen-type spacetimes, can be obtained from Rastall gravity. To achieve these spacetimes, the authors consider the presence of a phantom scalar field with nonlinear electrodynamics. However, in this comment, we obtained different electromagnetic Lagrangians from the original work. The most problematic issue is not the incorrect expression of the electromagn…

This https://arxiv.org/abs/2301.04863 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Choosing observation operators to mitigate model error in Bayesian inverse problems
In statistical inference, a discrepancy between the parameter-to-observable map that generates the data and the parameter-to-observable map that is used for inference can lead to misspecified likelihoods and thus to incorrect estimates. In many inverse problems, the parameter-to-observable map is the composition of a linear state-to-observable map called an `observation operator' and a possibly nonlinear parameter-to-state map called the `model'. We consider such Bayesian inverse problems where…

Finally tracked down why the broken status was broken - #Akkoma's media preview proxy defaults to on and ebay was having absolutely none of it when it tried to get information from there. Maybe it's a broken ebay URL but turning the proxy off made everything work and I can live with that rather than people being able to nerf my timeline by typing in incorrect URLs...

Max-Cut with $\epsilon$-Accurate Predictions
Vincent Cohen-Addad, Tommaso d'Orsi, Anupam Gupta, Euiwoong Lee, Debmalya Panigrahi
https://arxiv.org/abs/2402.18263

Max-Cut with $ε$-Accurate Predictions
We study the approximability of the MaxCut problem in the presence of predictions. Specifically, we consider two models: in the noisy predictions model, for each vertex we are given its correct label in $\{-1,+1\}$ with some unknown probability $1/2 + ε$, and the other (incorrect) label otherwise. In the more-informative partial predictions model, for each vertex we are given its correct label with probability $ε$ and no label otherwise. We assume only pairwise independence between vertices i…

A Multimodal Handover Failure Detection Dataset and Baselines
Santosh Thoduka, Nico Hochgeschwender, Juergen Gall, Paul G. Pl\"oger
https://arxiv.org/abs/2402.18319

A Multimodal Handover Failure Detection Dataset and Baselines
An object handover between a robot and a human is a coordinated action which is prone to failure for reasons such as miscommunication, incorrect actions and unexpected object properties. Existing works on handover failure detection and prevention focus on preventing failures due to object slip or external disturbances. However, there is a lack of datasets and evaluation methods that consider unpreventable failures caused by the human participant. To address this deficit, we present the multimod…

This https://arxiv.org/abs/2301.11751 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Manifolds with trivial Chern classes II: Manifolds Isogenous to a Torus Product, coframed Manifolds and a question by Baldassarri
Motivated by a general question addressed by Mario Baldassarri in 1956, we discuss characterizations of the Pseudo-Abelian Varieties introduced by Roth, and we introduce a first new notion, of Manifolds Isogenous to a k-Torus Product: the latter have the last k Chern classes trivial in rational cohomology and vanishing Chern numbers. We show that in dimension 2 the latter class is the correct substitute for some incorrect assertions by Enriques, Dantoni, Roth and Baldassarri: these are the surf…

When to Trust LLMs: Aligning Confidence with Response Quality
Shuchang Tao, Liuyi Yao, Hanxing Ding, Yuexiang Xie, Qi Cao, Fei Sun, Jinyang Gao, Huawei Shen, Bolin Ding
https://arxiv.org/abs/2404.17287

When to Trust LLMs: Aligning Confidence with Response Quality
Despite the success of large language models (LLMs) in natural language generation, much evidence shows that LLMs may produce incorrect or nonsensical text. This limitation highlights the importance of discerning when to trust LLMs, especially in safety-critical domains. Existing methods, which rely on verbalizing confidence to tell the reliability by inducing top-k responses and sampling-aggregating multiple responses, often fail, due to the lack of objective guidance of confidence. To address…

This https://arxiv.org/abs/2404.01276 has been replaced.
link: https://scholar.google.com/scholar?q=a

Variable-Length Stop-Feedback Coding for Minimum Age of Incorrect Information
The Age of Incorrect Information (AoII) is examined within the context of remote monitoring of a Markov source using variable-length stop-feedback (VLSF) coding. Leveraging recent results on the non-asymptotic channel coding rate, we consider sources with small cardinality, where feedback is non-instantaneous as the transmitted information and feedback message have comparable lengths. We focus on the feedback sequence, i.e. the times of feedback transmissions, and derive AoII-optimal and delay-…

Validating a lutetium frequency reference
Kyle J. Arnold, Scott Bustabad, Qin Qichen, Zhao Zhang, Qi Zhao, Murray D. Barrett
https://arxiv.org/abs/2404.16414 https://arxiv.org/pdf/2404.16414
arXiv:2404.16414v1 Announce Type: new
Abstract: We review our progress in developing a frequency reference with singly ionized lutetium and give estimates of the levels of inaccuracy we expect to achieve in the near future with both the $^1S_0\leftrightarrow{}^3D_1$ and $^1S_0\leftrightarrow{}^3D_2$ transitions. Based on established experimental results, we show that inaccuracies at the low $10^{-19}$ level are readily achievable for the $^1S_0\leftrightarrow{}^3D_1$ transition, and the frequency ratio between the two transitions is limited almost entirely by the BBR shift. We argue that the frequency ratio measured within the one apparatus provides a well-defined metric to compare and establish the performance of remotely located systems. For the measurement of an in situ frequency ratio, relativistic shifts drop out and both transitions experience the same electromagnetic environment. Consequently, the uncertainty budget for the ratio is practically identical to the uncertainty budgets for the individual transitions. If the ratios for two or more systems disagree we can be certain at least one of the clock assessments is incorrect. If they agree, subsequent comparisons on one transition would only differ by relativistic effects. Since motional effects are easily assessed and typically small for a heavy ion, only the differential gravitational red-shift will significantly contribute and this can be confirmed by comparison on the second transition.

Visual Hallucinations of Multi-modal Large Language Models
Wen Huang, Hongbin Liu, Minxin Guo, Neil Zhenqiang Gong
https://arxiv.org/abs/2402.14683 https:/…

Visual Hallucinations of Multi-modal Large Language Models
Visual hallucination (VH) means that a multi-modal LLM (MLLM) imagines incorrect details about an image in visual question answering. Existing studies find VH instances only in existing image datasets, which results in biased understanding of MLLMs' performance under VH due to limited diversity of such VH instances. In this work, we propose a tool called VHTest to generate a diverse set of VH instances. Specifically, VHTest finds some initial VH instances in existing image datasets (e.g., COCO)…

Kinetic theory of vacuum pair production in uniform electric fields revisited
I. A. Aleksandrov, A. Kudlis, A. I. Klochai
https://arxiv.org/abs/2403.17204 …

Kinetic theory of vacuum pair production in uniform electric fields revisited
We investigate the phenomenon of electron-positron pair production from vacuum in the presence of a uniform time-dependent electric field of arbitrary polarization. Taking into account the interaction with the external classical background in a nonperturbative manner, we quantize the electron-positron field and derive a system of ten quantum kinetic equations (QKEs) showing that the previously-used QKEs are incorrect once the external field rotates in space. We employ then the Wigner-function f…

This https://arxiv.org/abs/2303.00202 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

PatchZero: Zero-Shot Automatic Patch Correctness Assessment
Automated Program Repair (APR) techniques have shown more and more promising results in fixing real-world bugs. Despite the effectiveness, APR techniques still face an overfitting problem: a generated patch can be incorrect although it passes all tests. It is time-consuming to manually evaluate the correctness of generated patches that can pass all tests. To address this problem, many approaches have been proposed to automatically assess the correctness of patches generated by APR techniques. T…

This https://arxiv.org/abs/2401.11314 has been replaced.
link: https://scholar.google.com/scholar?q=a

CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs
Timely, personalized feedback is essential for students learning programming. LLM-powered tools like ChatGPT offer instant support, but reveal direct answers with code, which may hinder deep conceptual engagement. We developed CodeAid, an LLM-powered programming assistant delivering helpful, technically correct responses, without revealing code solutions. CodeAid answers conceptual questions, generates pseudo-code with line-by-line explanations, and annotates student's incorrect code with fix s…

Enhanced Bayesian Personalized Ranking for Robust Hard Negative Sampling in Recommender Systems
Kexin Shi, Jing Zhang, Linjiajie Fang, Wenjia Wang, Bingyi Jing
https://arxiv.org/abs/2403.19276

Enhanced Bayesian Personalized Ranking for Robust Hard Negative Sampling in Recommender Systems
In implicit collaborative filtering, hard negative mining techniques are developed to accelerate and enhance the recommendation model learning. However, the inadvertent selection of false negatives remains a major concern in hard negative sampling, as these false negatives can provide incorrect information and mislead the model learning. To date, only a small number of studies have been committed to solve the false negative problem, primarily focusing on designing sophisticated sampling algorit…

This https://arxiv.org/abs/2403.18346 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Quantifying and Mitigating Unimodal Biases in Multimodal Large Language Models: A Causal Perspective
Recent advancements in Large Language Models (LLMs) have facilitated the development of Multimodal LLMs (MLLMs). Despite their impressive capabilities, MLLMs often suffer from an over-reliance on unimodal biases (e.g., language bias and vision bias), leading to incorrect answers in complex multimodal tasks. To investigate this issue, we propose a causal framework to interpret the biases in Visual Question Answering (VQA) problems. Within our framework, we devise a causal graph to elucidate the …

This https://arxiv.org/abs/2312.04902 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

BELT: Old-School Backdoor Attacks can Evade the State-of-the-Art Defense with Backdoor Exclusivity Lifting
Deep neural networks (DNNs) are susceptible to backdoor attacks, where malicious functionality is embedded to allow attackers to trigger incorrect classifications. Old-school backdoor attacks use strong trigger features that can easily be learned by victim models. Despite robustness against input variation, the robustness however increases the likelihood of unintentional trigger activations. This leaves traces to existing defenses, which find approximate replacements for the original triggers t…

This https://arxiv.org/abs/2306.09541 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Validating AI-Generated Code with Live Programming
AI-powered programming assistants are increasingly gaining popularity, with GitHub Copilot alone used by over a million developers worldwide. These tools are far from perfect, however, producing code suggestions that may be incorrect in subtle ways. As a result, developers face a new challenge: validating AI's suggestions. This paper explores whether Live Programming (LP), a continuous display of a program's runtime values, can help address this challenge. To answer this question, we built a Py…

Comment on "Source of black bounces in Rastall gravity''
Manuel E. Rodrigues, Marcos V. de S. Silva
https://arxiv.org/abs/2402.17814 https://<…

Comment on "Source of black bounces in Rastall gravity''
In Atazadeh and Hadi (JCAP \textbf{01}, 067 (2024)), the authors proposed that black bounce solutions, such as the Simpson-Visser and the Bardeen-type spacetimes, can be obtained from Rastall gravity. To achieve these spacetimes, the authors consider the presence of a phantom scalar field with nonlinear electrodynamics. However, in this comment, we obtained different electromagnetic Lagrangians from the original work. The most problematic issue is not the incorrect expression of the electromagn…

This https://arxiv.org/abs/2403.04260 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Can Small Language Models be Good Reasoners for Sequential Recommendation?
Large language models (LLMs) open up new horizons for sequential recommendations, owing to their remarkable language comprehension and generation capabilities. However, there are still numerous challenges that should be addressed to successfully implement sequential recommendations empowered by LLMs. Firstly, user behavior patterns are often complex, and relying solely on one-step reasoning from LLMs may lead to incorrect or task-irrelevant responses. Secondly, the prohibitively resource requir…

This https://arxiv.org/abs/2403.04745 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A General Calibrated Regret Metric for Detecting and Mitigating Human-Robot Interaction Failures
Robot decision-making increasingly relies on expressive data-driven human prediction models when operating around people. While these models are known to suffer from prediction errors in out-of-distribution interactions, not all prediction errors equally impact downstream robot performance. We identify that the mathematical notion of regret precisely characterizes the degree to which incorrect predictions of future interaction outcomes degraded closed-loop robot performance. However, canonical …

Comment on "Source of black bounces in Rastall gravity''
Manuel E. Rodrigues, Marcos V. de S. Silva
https://arxiv.org/abs/2402.17814 https://<…

Comment on "Source of black bounces in Rastall gravity''
In Atazadeh and Hadi (JCAP \textbf{01}, 067 (2024)), the authors proposed that black bounce solutions, such as the Simpson-Visser and the Bardeen-type spacetimes, can be obtained from Rastall gravity. To achieve these spacetimes, the authors consider the presence of a phantom scalar field with nonlinear electrodynamics. However, in this comment, we obtained different electromagnetic Lagrangians from the original work. The most problematic issue is not the incorrect expression of the electromagn…

This https://arxiv.org/abs/2404.10357 has been replaced.
link: https://scholar.google.com/scholar?q=a

Optimization of Prompt Learning via Multi-Knowledge Representation for Vision-Language Models
Vision-Language Models (VLMs), such as CLIP, play a foundational role in various cross-modal applications. To fully leverage VLMs' potential in adapting to downstream tasks, context optimization methods like Prompt Tuning are essential. However, one key limitation is the lack of diversity in prompt templates, whether they are hand-crafted or learned through additional modules. This limitation restricts the capabilities of pretrained VLMs and can result in incorrect predictions in downstream tas…

This https://arxiv.org/abs/2404.07572 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Fragile Model Watermark for integrity protection: leveraging boundary volatility and sensitive sample-pairing
Neural networks have increasingly influenced people's lives. Ensuring the faithful deployment of neural networks as designed by their model owners is crucial, as they may be susceptible to various malicious or unintentional modifications, such as backdooring and poisoning attacks. Fragile model watermarks aim to prevent unexpected tampering that could lead DNN models to make incorrect decisions. They ensure the detection of any tampering with the model as sensitively as possible.However, prior …

This https://arxiv.org/abs/2403.10822 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Do Large Language Models understand Medical Codes?
The overarching goal of recent AI research has been to make steady progress towards achieving Artificial General Intelligence (AGI), prompting the evaluation of Large Language Models (LLMs) across a variety of tasks and domains. One such domain is healthcare, where LLMs can greatly benefit clinical practice by assisting with a wide range of tasks. However, these models are also prone to producing "hallucinations" or incorrect responses when faced with queries they cannot adequately address, rai…

This https://arxiv.org/abs/2404.10357 has been replaced.
link: https://scholar.google.com/scholar?q=a

Optimization of Prompt Learning via Multi-Knowledge Representation for Vision-Language Models
Vision-Language Models (VLMs), such as CLIP, play a foundational role in various cross-modal applications. To fully leverage VLMs' potential in adapting to downstream tasks, context optimization methods like Prompt Tuning are essential. However, one key limitation is the lack of diversity in prompt templates, whether they are hand-crafted or learned through additional modules. This limitation restricts the capabilities of pretrained VLMs and can result in incorrect predictions in downstream tas…

On (Mis)perceptions of testing effectiveness: an empirical study
Sira Vegas, Patricia Riofrio, Esperanza Marcos, Natalia Juristo
https://arxiv.org/abs/2402.07222

On (Mis)perceptions of testing effectiveness: an empirical study
A recurring problem in software development is incorrect decision making on the techniques, methods and tools to be used. Mostly, these decisions are based on developers' perceptions about them. A factor influencing people's perceptions is past experience, but it is not the only one. In this research, we aim to discover how well the perceptions of the defect detection effectiveness of different techniques match their real effectiveness in the absence of prior experience. To do this, we conduct …

This https://arxiv.org/abs/2311.04205 has been replaced.
link: https://scholar.google.com/scholar?q=a

Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
Misunderstandings arise not only in interpersonal communication but also between humans and Large Language Models (LLMs). Such discrepancies can make LLMs interpret seemingly unambiguous questions in unexpected ways, yielding incorrect responses. While it is widely acknowledged that the quality of a prompt, such as a question, significantly impacts the quality of the response provided by LLMs, a systematic method for crafting questions that LLMs can better comprehend is still underdeveloped. In…

This https://arxiv.org/abs/2402.10773 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

AIM: Automated Input Set Minimization for Metamorphic Security Testing
For Web systems, which are accessible to any machine connected to internet, security is a critical concern. Although security testing can be automated by generating crafted inputs as an attacker would do, solutions to automate the test oracle, i.e., distinguishing correct from incorrect outputs for a given input, remain preliminary. Specifically, previous work has demonstrated the potential of metamorphic testing; indeed, security failures can be determined by metamorphic relations that turn va…

This https://arxiv.org/abs/2402.10773 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

AIM: Automated Input Set Minimization for Metamorphic Security Testing
For Web systems, which are accessible to any machine connected to internet, security is a critical concern. Although security testing can be automated by generating crafted inputs as an attacker would do, solutions to automate the test oracle, i.e., distinguishing correct from incorrect outputs for a given input, remain preliminary. Specifically, previous work has demonstrated the potential of metamorphic testing; indeed, security failures can be determined by metamorphic relations that turn va…

This https://arxiv.org/abs/2404.02124 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models
Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable format in assessments and practices. One of the most important aspects of MCQs is the distractors, i.e., incorrect options that are designed to target common errors or misconceptions among real students. To date, the task of crafting high-quality distractors largely remains a labor and time-intensive process for teachers and learning content designers, w…

AIM: Automated Input Set Minimization for Metamorphic Security Testing
Nazanin Bayati Chaleshtari, Yoann Marquer, Fabrizio Pastore, Lionel C. Briand
https://arxiv.org/abs/2402.10773

AIM: Automated Input Set Minimization for Metamorphic Security Testing
For Web systems, which are accessible to any machine connected to internet, security is a critical concern. Although security testing can be automated by generating crafted inputs as an attacker would do, solutions to automate the test oracle, i.e., distinguishing correct from incorrect outputs for a given input, remain preliminary. Specifically, previous work has demonstrated the potential of metamorphic testing; indeed, security failures can be determined by metamorphic relations that turn va…

AIM: Automated Input Set Minimization for Metamorphic Security Testing
Nazanin Bayati Chaleshtari, Yoann Marquer, Fabrizio Pastore, Lionel C. Briand
https://arxiv.org/abs/2402.10773

AIM: Automated Input Set Minimization for Metamorphic Security Testing
For Web systems, which are accessible to any machine connected to internet, security is a critical concern. Although security testing can be automated by generating crafted inputs as an attacker would do, solutions to automate the test oracle, i.e., distinguishing correct from incorrect outputs for a given input, remain preliminary. Specifically, previous work has demonstrated the potential of metamorphic testing; indeed, security failures can be determined by metamorphic relations that turn va…