Tootfinder

Österreichs AMS-Chatbot teurer – aber weniger Bias
Der Berufsinfomat des Arbeitsmarktservice in Österreich ist verbessert worden. Dafür kostet der Betrieb auch deutlich mehr als geplant war.
https://www.…

Uri Berliner's essay about NPR reignited criticism of the outlet on social media, especially among conservatives, and vehement pushback from some staffers (New York Times)
https://www.nytimes.com/2024/04/11/business/media/npr-criticism-liberal…

NPR in Turmoil After It Is Accused of Liberal Bias
An essay from an editor at the broadcaster has generated a firestorm of criticism about the network on social media, especially among conservatives.

Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought
James Chua, Edward Rees, Hunar Batra, Samuel R. Bowman, Julian Michael, Ethan Perez, Miles Turpin
https://arxiv.org/abs/2403.05518

Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought
While chain-of-thought prompting (CoT) has the potential to improve the explainability of language model reasoning, it can systematically misrepresent the factors influencing models' behavior--for example, rationalizing answers in line with a user's opinion without mentioning this bias. To mitigate this biased reasoning problem, we introduce bias-augmented consistency training (BCT), an unsupervised fine-tuning scheme that trains models to give consistent reasoning across prompts with and witho…

A New Testing Method for Justification Bias Using High-Frequency Data of Health and Employment
Jiayi Wen, Zixi Ye, Xuan Zhang
https://arxiv.org/abs/2403.06368

A New Testing Method for Justification Bias Using High-Frequency Data of Health and Employment
Justification bias, wherein retirees may report poorer health to rationalize their retirement, poses a major concern to the widely-used measure of self-assessed health in retirement studies. This paper introduces a novel method for testing the presence of this bias in the spirit of regression discontinuity. The underlying idea is that any sudden shift in self-assessed health immediately following retirement is more likely attributable to the bias. Our strategy is facilitated by a unique high-fr…

The obvious bias on this poll, if it even gets statistically significant votes at all, is that people with so many followers that it's annoying to get replies don't follow me and so won't see it to vote No as much as you'd otherwise expect.

Uri Berliner's essay about NPR reignited criticism of the outlet on social media, especially among conservatives, and vehement pushback from some staffers (New York Times)
https://www.nytimes.com/2024/04/11/business/media/npr-criticism-liberal…

NPR in Turmoil After It Is Accused of Liberal Bias
An essay from an editor at the broadcaster has generated a firestorm of criticism about the network on social media, especially among conservatives.

At yesterday's "AI town hall" journalist and historian Michael Socolow argued that new media have always disrupted politics, from the penny press and telegraph to radio and TV. Now that social media have prioritized confirmation bias over persuasion, will voters be less likely to question AI-generated fakery?

When is an Arctic bias not an Arctic bias?
I was going to blog about this cool new paper that my colleagues at DMI have produced, but John Kennedy has as always done such a good job I will just point you over there... Wondering whether a warm bias in the Arctic in ERA5 affects our estimates of global temperature change. When is an Arctic bias not an Arctic bias?

This https://arxiv.org/abs/2305.13931 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Improving position bias estimation against sparse and skewed dataset with item embedding
Estimating position bias is a well-known challenge in Learning to Rank (L2R). Click data in e-commerce applications, such as targeted advertisements and search engines, provides implicit but abundant feedback to improve personalized rankings. However, click data inherently includes various biases like position bias. Based on the position-based click model, Result Randomization and Regression Expectation-Maximization algorithm (REM) have been proposed to estimate position bias, but they require …

Incel CS lecturer at Waterloo
$2.4.1 DIFFICULTIES OF HUNTING AT WORK"
I don't know what to say
"In academia, dating and romantic/sexual relationship between professors and students is controversial"
Yes. Yes it is.
"There is clearly a world-wide bias in judgmental decisions for accusing males, compared to females, in harassments. It may be because males usually ask out and show interest in females and females may take it as an offense."
Okay so has anyone explained to you the concept of power dynamics and unethical abuse of authority roles?
"A funny thing is that once, in a seminar for teaching assistants in the University of Waterloo, they told us that teaching
assistants should not date students. I asked about the case of John Nash. The professor answered me that they married
after the student graduated (which I think is not true). Then, I answered even if that is true, did they suddenly get
married without any dating? Of course, they dated before that, while she was a student! I think they themselves know
that this rule is nonfunctional because if the professor/instructor and the student are both single, they may like each
other or fall in love as they interact frequently in the school. This rule was even criticised in the American comedy show "Friends" (season 6, episode 18)."
Ok, there's a lot to unpack here, but the main bit is this: Do you understand that the sitcom "Friends" is not a good source for understanding ethics?

Paving the Way for Pass Disturb Free Vertical NAND Storage via A Dedicated and String-Compatible Pass Gate
Zijian Zhao, Sola Woo, Khandker Akif Aabrar, Sharadindu Gopal Kirtania, Zhouhang Jiang, Shan Deng, Yi Xiao, Halid Mulaosmanovic, Stefan Duenkel, Dominik Kleimaier, Steven Soss, Sven Beyer, Rajiv Joshi, Scott Meninger, Mohamed Mohamed, Kijoon Kim, Jongho Woo, Suhwan Lim, Kwangsoo Kim, Wanki Kim, Daewon Ha, Vijaykrishnan Narayanan, Suman Datta, Shimeng Yu, Kai Ni

Paving the Way for Pass Disturb Free Vertical NAND Storage via A Dedicated and String-Compatible Pass Gate
In this work, we propose a dual-port cell design to address the pass disturb in vertical NAND storage, which can pass signals through a dedicated and string-compatible pass gate. We demonstrate that: i) the pass disturb-free feature originates from weakening of the depolarization field by the pass bias at the high-${V}_{TH}$ (HVT) state and the screening of the applied field by channel at the low-${V}_{TH}$ (LVT) state; ii) combined simulations and experimental demonstrations of dual-port desig…

On the influence of the Galois group structure on the Chebyshev bias in number fields
Mounir Hayani (IMB)
https://arxiv.org/abs/2404.06804 https://<…

On the influence of the Galois group structure on the Chebyshev bias in number fields
In this paper we produce unconditionally new instances of Galois number field extensions exhibiting strong discrepancies in the distribution of Frobenius elements among conjugacy classes of the Galois group. We first prove an inverse Galois theoretic statement showing a dichotomy between ``extreme Chebyshev biases'' and ``equal prime ideal counting''. We further introduce a group theoretic property that implies extreme biases. In the case of abelian extensions this leads to a complete character…

Thermal cycling induced evolution and colossal exchange bias in MnPS3/Fe3GeTe2 van der Waals heterostructures
Aravind Puthirath Balan, Aditya Kumar, Patrick Reiser, Joseph Vas, Thibaud Denneulin, Khoa Dang Lee, Tom G Saunderson, M\"arta Tschudin, Clement Pellet-Mary, Debarghya Dutta, Carolin Schrader, Tanja Scholz, Jaco Geuchies, Shuai Fu, Hai Wang, Alberta Bonanni, Bettina V. Lotsch, Ulrich Nowak, Gerhard Jakob, Jacob Gayles, Andras Kovacs, Rafal E. Dunin-Borkowski, Patrick Malet…

Thermal cycling induced evolution and colossal exchange bias in MnPS3/Fe3GeTe2 van der Waals heterostructures
The exchange bias phenomenon, inherent in exchange-coupled ferromagnetic and antiferromagnetic systems, has intrigued researchers for decades. Van der Waals materials, with their layered structure, provide an optimal platform for probing such physical phenomena. However, achieving a facile and effective means to manipulate exchange bias in pristine van der Waals heterostructures remains challenging. In this study, we investigate the origin of exchange bias in MnPS3/Fe3GeTe2 van der Waals hetero…

This https://arxiv.org/abs/2311.11321 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
State-of-the-art methods for conditional average treatment effect (CATE) estimation make widespread use of representation learning. Here, the idea is to reduce the variance of the low-sample CATE estimation by a (potentially constrained) low-dimensional representation. However, low-dimensional representations can lose information about the observed confounders and thus lead to bias, because of which the validity of representation learning for CATE estimation is typically violated. In this paper…

This https://arxiv.org/abs/2404.03778 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincaré Ball
Hierarchy is a natural representation of semantic taxonomies, including the ones routinely used in image segmentation. Indeed, recent work on semantic segmentation reports improved accuracy from supervised training leveraging hierarchical label structures. Encouraged by these results, we revisit the fundamental assumptions behind that work. We postulate and then empirically verify that the reasons for the observed improvement in segmentation accuracy may be entirely unrelated to the use of the …

Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought
James Chua, Edward Rees, Hunar Batra, Samuel R. Bowman, Julian Michael, Ethan Perez, Miles Turpin
https://arxiv.org/abs/2403.05518

Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought
While chain-of-thought prompting (CoT) has the potential to improve the explainability of language model reasoning, it can systematically misrepresent the factors influencing models' behavior--for example, rationalizing answers in line with a user's opinion without mentioning this bias. To mitigate this biased reasoning problem, we introduce bias-augmented consistency training (BCT), an unsupervised fine-tuning scheme that trains models to give consistent reasoning across prompts with and witho…

A Probabilistic Hadamard U-Net for MRI Bias Field Correction
Xin Zhu, Hongyi Pan, Yury Velichko, Adam B. Murphy, Ashley Ross, Baris Turkbey, Ahmet Enis Cetin, Ulas Bagci
https://arxiv.org/abs/2403.05024

A Probabilistic Hadamard U-Net for MRI Bias Field Correction
Magnetic field inhomogeneity correction remains a challenging task in MRI analysis. Most established techniques are designed for brain MRI by supposing that image intensities in the identical tissue follow a uniform distribution. Such an assumption cannot be easily applied to other organs, especially those that are small in size and heterogeneous in texture (large variations in intensity), such as the prostate. To address this problem, this paper proposes a probabilistic Hadamard U-Net (PHU-Net…

Sensitivity analysis for publication bias in meta-analysis of sparse data based on exact likelihood
Taojun Hu, Yi Zhou, Sattoshi Hattori
https://arxiv.org/abs/2404.06837

Sensitivity analysis for publication bias in meta-analysis of sparse data based on exact likelihood
Meta-analysis is a powerful tool to synthesize findings from multiple studies. The normal-normal random-effects model is widely used accounting for between-study heterogeneity. However, meta-analysis of sparse data, which may arise when the event rate is low for binary or count outcomes, poses a challenge to the normal-normal random-effects model in the accuracy and stability in inference since the normal approximation in the within-study likelihood may not be good. To reduce bias arising from …

Big glowing signs every other block on the side of the road, and prices at the grocery store, feel impactful.
From: @…
https://journa.host/@michellemanafy/11<…

Tests show GPT 3.5 systematically produces biases that disadvantage protected groups based on their names alone when screening and ranking candidates for jobs (Bloomberg)
https://www.bloomberg.com/graphics/2024-openai-gpt-hiring-racial-discriminati…

OpenAI GPT Sorts Resume Names With Racial Bias, Test Shows
Recruiters are eager to use generative AI, but a Bloomberg experiment found bias against job candidates based on their names alone

This https://arxiv.org/abs/2401.04698 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Caustic and hydrostatic mass bias: Implications for modified gravity
We propose and perform a joint analysis of the two different mass estimates of galaxy clusters, namely the hydrostatic and caustic techniques. Firstly, we show comprehensively that the mass bias between these two techniques can be possibly alleviated when cluster-specific assumptions constrained using the hydrostatic technique are utilized within the caustic technique. While at face value this demotes the caustic technique from a completely independent method, this allows one to further tighten…

A Two-Level Thermal Cycling-aware Task Mapping Technique for Reliability Management in Manycore Systems
Fatemeh Hossein Khani, Omid Akbari, Muhammad Shafique
https://arxiv.org/abs/2403.06134

A Two-Level Thermal Cycling-aware Task Mapping Technique for Reliability Management in Manycore Systems
Reliability management is one of the primary concerns in manycore systems design. Different aging mechanisms such as Negative-Bias Temperature Instability (NBTI), Electromigration (EM), and thermal cycling can reduce the reliability of these systems. However, state-of-the-art works mainly focused on NBTI and EM, whereas a few works have considered the thermal cycling effect. The thermal cycling effect can significantly aggravate the systems lifetime. Moreover, the thermal effects of cores on ea…

“I have invented a random number generator that companies put into everything. Banks might use it to generate your account balance. Doctors might use it to choose prescription strengths. My random number generator is inevitable. Society will have to navigate it.”

Sam Altman Answers The Burning Questions About AI: Bias, Privacy, Etc.
Responding, Altman criticized the construct of having people rate their doomsday predictions from one to 100.

Private Count Release: A Simple and Scalable Approach for Private Data Analytics
Ryan Rogers
https://arxiv.org/abs/2403.05073 https://

Private Count Release: A Simple and Scalable Approach for Private Data Analytics
We present a data analytics system that ensures accurate counts can be released with differential privacy and minimal onboarding effort while showing instances that outperform other approaches that require more onboarding effort. The primary difference between our proposal and existing approaches is that it does not rely on user contribution bounds over distinct elements, i.e. $\ell_0$-sensitivity bounds, which can significantly bias counts. Contribution bounds for $\ell_0$-sensitivity have bee…

This https://arxiv.org/abs/2303.16281 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

A "Perspectival" Mirror of the Elephant: Investigating Language Bias on Google, ChatGPT, YouTube, and Wikipedia
Contrary to Google Search's mission of delivering information from "many angles so you can form your own understanding of the world," we find that Google and its most prominent returned results - Wikipedia and YouTube - simply reflect a narrow set of culturally dominant views tied to the search language for complex topics like "Buddhism," "Liberalism," "colonization," "Iran" and "America." Simply stated, they present, to varying degrees, distinct information across the same search in different …

The AstraLux-TESS high-spatial resolution imaging survey. Search for stellar companions of 215 planet candidates from TESS
J. Lillo-Box, M. Morales-Calder\'on, D. Barrado, O. Balsalobre-Ruza, A. Castro-Gonz\'alez, I. Mendigut\'ia, N. Hu\'elamo, B. Montesinos, M. Vioque
https://arxiv.org/abs/2404.06316

The AstraLux-TESS high-spatial resolution imaging survey. Search for stellar companions of 215 planet candidates from TESS
Chance-aligned sources or blended companions can cause false positives in planetary transit detections or simply bias the determination of the candidate properties. In the era of high-precision space-based photometers, the need for high-spatial resolution images has demonstrated to be critical for validating and confirming transit signals. This already applied to the Kepler mission, it is now applicable to the TESS survey and will be critical for PLATO. We present the results of the AstraLux-TE…

Identifying plasma fractionation processes in the chromosphere using IRIS
David M. Long, Deborah Baker, Andy S. H. To, Lidia van Driel-Gesztelyi, David H. Brooks, Marco Stangalini, Mariarita Murabito, Alexander W. James, Mihalis Mathioudakis, Paola Testa
https://arxiv.org/abs/2403.06711 …

Identifying plasma fractionation processes in the chromosphere using IRIS
The composition of the solar corona differs from that of the photosphere, with the plasma thought to fractionate in the solar chromosphere according to the First Ionisation Potential (FIP) of the different elements. This produces a FIP bias, wherein elements with a low FIP are preferentially enhanced in the corona compared to their photospheric abundance, but direct observations of this process remain elusive. Here we use a series of spectroscopic observations of Active Region AR 12759 as it tr…

Distributed Least Squares in Small Space via Sketching and Bias Reduction
Sachin Garg, Kevin Tan, Micha{\l} Derezi\'nski
https://arxiv.org/abs/2405.05343

Distributed Least Squares in Small Space via Sketching and Bias Reduction
Matrix sketching is a powerful tool for reducing the size of large data matrices. Yet there are fundamental limitations to this size reduction when we want to recover an accurate estimator for a task such as least square regression. We show that these limitations can be circumvented in the distributed setting by designing sketching methods that minimize the bias of the estimator, rather than its error. In particular, we give a sparse sketching method running in optimal space and current matrix …

✌🏿 Uber Eats courier’s fight against AI bias shows justice under UK law is hard won
#uber…

Uber Eats courier's fight against AI bias shows justice under UK law is hard won | TechCrunch
On Tuesday, the BBC reported that Uber Eats courier Pa Edrissa Manjang, who is Black, had received a payout from Uber after "racially discriminatory" News this week that an Uber Eats courier accepted a payout to settle legal action after accusing the company of unlawful racial discrimination -- following repeated failures of its facial recognition checks -- raises questions about how fit for purpose UK law is to deal with rising use of AI systems.

Auditing health-related recommendations in social media: A Case Study of Abortion on YouTube
Mohammed Lahsaini, Mohamed Lechiakh, Alexandre Maurer
https://arxiv.org/abs/2404.07896

Auditing health-related recommendations in social media: A Case Study of Abortion on YouTube
Recommendation algorithms (RS) used by social media, like YouTube, significantly shape our information consumption across various domains, especially in healthcare. Hence, algorithmic auditing becomes crucial to uncover their potential bias and misinformation, particularly in the context of controversial topics like abortion. We introduce a simple yet effective sock puppet auditing approach to investigate how YouTube recommends abortion-related videos to individuals with different backgrounds. …

Size-induced Exchange Bias in Single-phase CoO Nanoparticles
Vikash Sharma, Sudip Pal, Divya Sharma, Dinesh Kumar Shukla, Ram Janay Chaudhary, Gunadhor Singh Okram
https://arxiv.org/abs/2404.06876

Size-induced Exchange Bias in Single-phase CoO Nanoparticles
We report EB in single-phase CoO nanoparticles, where two magnetic phases naturally emerge as the crystallite size decreases from 34.6 to 10.8 nm. The Néel temperature (TN) associated with antiferromagnetic ordering decreases monotonically with the reduction in crystallite size, highlighting the significant influence of size effects. The 34.6 nm nanoparticles exhibit magnetization irreversibility between zero field cooled (ZFC) and field-cooled (FC) states below TN. This irreversibility appear…

This https://arxiv.org/abs/2312.11468 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Bias-Reduced Neural Networks for Parameter Estimation in Quantitative MRI
Purpose: To develop neural network (NN)-based quantitative MRI parameter estimators with minimal bias and a variance close to the Cramér-Rao bound. Theory and Methods: We generalize the mean squared error loss to control the bias and variance of the NN's estimates, which involves averaging over multiple noise realizations of the same measurements during training. Bias and variance properties of the resulting NNs are studied for two neuroimaging applications. Results: In simulations, the pr…

Observation of an unconventional giant negative exchange bias effect in La$_{0.5}$Sr$_{0.5}$Co$_{0.85}$Nb$_{0.15}$O$_3$
Rishabh Shukla, B. Schwarz, R. S. Dhaka
https://arxiv.org/abs/2405.05053

Observation of an unconventional giant negative exchange bias effect in La$_{0.5}$Sr$_{0.5}$Co$_{0.85}$Nb$_{0.15}$O$_3$
We find an unconventional giant negative exchange bias (EB) of $H_{\rm EB}$ = --14.1~kOe at 2~K (cooling field of 50~kOe) in the cluster spin-glass (CSG) La$_{0.5}$Sr$_{0.5}$Co$_{0.85}$Nb$_{0.15}$O$_3$ perovsikte cobaltites. The magnetic memory effect, aging measurements, and nonlineraity in specific heat capacity reveal the glassy magnetic state at low temperatures. Further, the detailed analysis of {\it ac-}magnetic susceptibility confirms the glassy state below $\sim$58~K and the obtained ch…

This should replace the car crash/surgeon story as the canonical example of implicit bias https://gay.lesaoras.xyz/objects/33864ffb-b26e-4c07-8d94-db152a0cd9b1

Unhinged AO3 tags😈🔞 (@unhingedA03@gay.lesaoras.xyz)
Being a lawyer is kinda gay like wdym your job is getting guys off??

This https://arxiv.org/abs/2310.16418 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Bour's theorem for helicoidal surfaces with singularities
In this paper, generalizing the techniques of Bour's theorem, we prove that every generic cuspidal edge, more generally, generic $n$-type edge, which is invariant under a helicoidal motion in Euclidean $3$-space admits non-trivial isometric deformations. As a corollary, several geometric invariants, such as the limiting normal curvature, the cusp-directional torsion, the higher order cuspidal curvature and the bias, are proved to be extrinsic invariants.

Policy-Guided Diffusion
Matthew Thomas Jackson, Michael Tryfan Matthews, Cong Lu, Benjamin Ellis, Shimon Whiteson, Jakob Foerster
https://arxiv.org/abs/2404.06356

Policy-Guided Diffusion
In many real-world settings, agents must learn from an offline dataset gathered by some prior behavior policy. Such a setting naturally leads to distribution shift between the behavior policy and the target policy being trained - requiring policy conservatism to avoid instability and overestimation bias. Autoregressive world models offer a different solution to this by generating synthetic, on-policy experience. However, in practice, model rollouts must be severely truncated to avoid compoundin…

This https://arxiv.org/abs/2404.05426 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Test-Time Zero-Shot Temporal Action Localization
Zero-Shot Temporal Action Localization (ZS-TAL) seeks to identify and locate actions in untrimmed videos unseen during training. Existing ZS-TAL methods involve fine-tuning a model on a large amount of annotated training data. While effective, training-based ZS-TAL approaches assume the availability of labeled data for supervised learning, which can be impractical in some applications. Furthermore, the training process naturally induces a domain bias into the learned model, which may adversely …

Precision premium transformation -- a high-precision astrometric solution based on the precision premium curve
Z. J. Zheng, Q. Y. Peng, F. R. Lin, D. Li, Y. Zheng
https://arxiv.org/abs/2403.05883

Precision premium transformation -- a high-precision astrometric solution based on the precision premium curve
Context. In Gaia era, atmospheric turbulence, which causes stochastic wander of a star image, is a fundamental limitation to the astrometric accuracy of ground-based optical imaging. However, the positional bias caused by turbulence (called turbulence error here) can be effectively reduced by measuring a target relative to another reference (a star or a fast-moving target) which locates in the range of only several tens of arcsec, since they suffer from similar turbulence errors. This phenomeno…

At a House hearing on "NPR bias", Republicans criticize NPR CEO's absence but some praise local stations, and witnesses call for decentralizing or defunding NPR (Tyler Falk/Current)
https://current.org/2024/05/house-hear…

House hearing on NPR bias brings criticism from Republicans, but praise for local stations
Rep. Cathy McMorris Rodgers said the committee will "investigate the allegations against NPR and take appropriate action."

Judge Cannon just showed her 'inexperience' or 'bias' in latest Trump hearing: expert - Raw Story
https://www.rawstory.com/judge-cannon-bias-inexperience/

Judge Cannon just showed her 'inexperience' or 'bias' in latest Trump hearing: expert
Judge Aileen Cannon, the jurist overseeing Donald Trump's criminal case over allegedly stashed confidential documents, showed that she's either in the bag for the former president or that she's too much of a novice on the bench to handle the momentous case, a former prosecutor said on Friday. Andrew...

This post is a good way to start thinking about the information economy that led us to a place where
a Republican judge helps delay accountability for stealing nuclear documents and storing them in a closet normally storing campaign swag.
This information economy creates an environment in which a former prosecutor like Aileen Cannon
either believes, or claims to believe, outlandish claims of bias and ill-treatment
solely because career national security officials — r…

How We Got to a Place Where Right Wingers Cheer Stealing Nuclear Documents - emptywheel
Trump's propaganda machine has drowned out facts and replaced it with grievance. And until something starts cutting through that grievance, mere trials aren't going to fix this.

This https://arxiv.org/abs/2310.16097 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Beware the recent past: a bias in spectral energy distribution modelling due to bursty star formation
We investigate how the recovery of galaxy star formation rates (SFRs) using energy-balance spectral energy distribution (SED) fitting codes depends on their recent star formation histories (SFHs). We use the Magphys and Prospector codes to fit 6,706 synthetic spectral energy distributions of simulated massive galaxies at $1 < z < 8$ from the Feedback in Realistic Environments (FIRE) project. We identify a previously-unknown systematic error in the Magphys results due to bursty star formation: t…

This https://arxiv.org/abs/2306.06450 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

Movement bias in asymmetric landscapes and its impact on population distribution and critical habitat size
Ecologists have long investigated how demographic and movement parameters determine the spatial distribution and critical habitat size of a population. However, most models oversimplify movement behavior, neglecting how landscape heterogeneity influences individual movement. We relax this assumption and introduce a reaction-advection-diffusion equation that describes population dynamics when individuals exhibit space-dependent movement bias toward preferred regions. Our model incorporates two t…

“I have invented a random number generator that companies put into everything. Banks might use it to generate your account balance. Doctors might use it to choose prescription strengths. My random number generator is inevitable. Society will have to navigate it.”

Sam Altman Answers The Burning Questions About AI: Bias, Privacy, Etc.
Responding, Altman criticized the construct of having people rate their doomsday predictions from one to 100.

This https://arxiv.org/abs/2309.06629 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

The Relational Bottleneck as an Inductive Bias for Efficient Abstraction
A central challenge for cognitive science is to explain how abstract concepts are acquired from limited experience. This has often been framed in terms of a dichotomy between connectionist and symbolic cognitive models. Here, we highlight a recently emerging line of work that suggests a novel reconciliation of these approaches, by exploiting an inductive bias that we term the relational bottleneck. In that approach, neural networks are constrained via their architecture to focus on relations be…

Private Count Release: A Simple and Scalable Approach for Private Data Analytics
Ryan Rogers
https://arxiv.org/abs/2403.05073 https://

Private Count Release: A Simple and Scalable Approach for Private Data Analytics
We present a data analytics system that ensures accurate counts can be released with differential privacy and minimal onboarding effort while showing instances that outperform other approaches that require more onboarding effort. The primary difference between our proposal and existing approaches is that it does not rely on user contribution bounds over distinct elements, i.e. $\ell_0$-sensitivity bounds, which can significantly bias counts. Contribution bounds for $\ell_0$-sensitivity have bee…

Can’t say I’m too surprised by the UKs trend development in the academic freedom index (I know, I know, confirmation bias).
And geez, I wonder what happened in 2016… https://academic-freedom-index.net/

This https://arxiv.org/abs/2312.13643 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Debiasing Welch's Method for Spectral Density Estimation
Welch's method provides an estimator of the power spectral density that is statistically consistent. This is achieved by averaging over periodograms calculated from overlapping segments of a time series. For a finite length time series, while the variance of the estimator decreases as the number of segments increase, the magnitude of the estimator's bias increases: a bias-variance trade-off ensues when setting the segment number. We address this issue by providing a novel method for debiasing W…

"Oil and Gas Companies Want You to Think They Care About Women — but It’s Just PR"
#Oil #Gas #FossilFuels #Energy

Oil and Gas Companies Want You to Think They Care About Women — but It’s Just PR
In a March 7 video posted to Shell’s LinkedIn page, a woman named Kimberly says to the camera,“Unconscious bias shows up everywhere, in all forms, and it is more prevalent than any of us would like to admit.”  In the supercut of Shell employee testimonials that follow, a woman named Jane declares that “still too […]

The AstraLux-TESS high-spatial resolution imaging survey. Search for stellar companions of 215 planet candidates from TESS
J. Lillo-Box, M. Morales-Calder\'on, D. Barrado, O. Balsalobre-Ruza, A. Castro-Gonz\'alez, I. Mendigut\'ia, N. Hu\'elamo, B. Montesinos, M. Vioque
https://arxiv.org/abs/2404.06316

The AstraLux-TESS high-spatial resolution imaging survey. Search for stellar companions of 215 planet candidates from TESS
Chance-aligned sources or blended companions can cause false positives in planetary transit detections or simply bias the determination of the candidate properties. In the era of high-precision space-based photometers, the need for high-spatial resolution images has demonstrated to be critical for validating and confirming transit signals. This already applied to the Kepler mission, it is now applicable to the TESS survey and will be critical for PLATO. We present the results of the AstraLux-TE…

Identifying plasma fractionation processes in the chromosphere using IRIS
David M. Long, Deborah Baker, Andy S. H. To, Lidia van Driel-Gesztelyi, David H. Brooks, Marco Stangalini, Mariarita Murabito, Alexander W. James, Mihalis Mathioudakis, Paola Testa
https://arxiv.org/abs/2403.06711 …

Identifying plasma fractionation processes in the chromosphere using IRIS
The composition of the solar corona differs from that of the photosphere, with the plasma thought to fractionate in the solar chromosphere according to the First Ionisation Potential (FIP) of the different elements. This produces a FIP bias, wherein elements with a low FIP are preferentially enhanced in the corona compared to their photospheric abundance, but direct observations of this process remain elusive. Here we use a series of spectroscopic observations of Active Region AR 12759 as it tr…

"Hundreds of millions of people have used generative #AI in the last two years. It promises immense benefits, but also serious risks related to bias, alleged copyright infringement, and non-consensual intimate imagery. AI companies, academic researchers, and civil society agree that #generativeAI syste…

This https://arxiv.org/abs/2402.13787 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Fairness Rising from the Ranks: HITS and PageRank on Homophilic Networks
In this paper, we investigate the conditions under which link analysis algorithms prevent minority groups from reaching high ranking slots. We find that the most common link-based algorithms using centrality metrics, such as PageRank and HITS, can reproduce and even amplify bias against minority groups in networks. Yet, their behavior differs: one one hand, we empirically show that PageRank mirrors the degree distribution for most of the ranking positions and it can equalize representation of m…

Wenn man Bilder mithilfe von KI generiert, dann sind die Menschen darauf meist um die 30. Ältere Menschen kommen gar nicht vor, es sei denn, man fragt explizit danach.
Dies ist der Bias, von dem permanent die Rede ist. Die meisten Bilder, die im Netz im Umlauf sind, sind halt von jungen Menschen – diese dienen dann als Vorlage für die KI-generierten Bilder.
#ki

Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support
Felix Haag, Carlo Stingl, Katrin Zerfass, Konstantin Hopf, Thorsten Staake
https://arxiv.org/abs/2405.04972

Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support
Information systems (IS) are frequently designed to leverage the negative effect of anchoring bias to influence individuals' decision-making (e.g., by manipulating purchase decisions). Recent advances in Artificial Intelligence (AI) and the explanations of its decisions through explainable AI (XAI) have opened new opportunities for mitigating biased decisions. So far, the potential of these technological advances to overcome anchoring bias remains widely unclear. To this end, we conducted two o…

2024 NFL mock draft ... with a twist! What every team SHOULD do in Round 1 https://www.nfl.com/news/2024-nfl-mock-draft-with-a-twist-what-every-team-should-do-in-round-1

2024 NFL mock draft ... with a twist! What every team SHOULD do in Round 1
There's no shortage of 2024 NFL mock drafts exploring what each team COULD do, but how about what everyone SHOULD do? Adam Rank simulates the first round with full bias. Check out all of his picks, 1-32.

Observation of an unconventional giant negative exchange bias effect in La$_{0.5}$Sr$_{0.5}$Co$_{0.85}$Nb$_{0.15}$O$_3$
Rishabh Shukla, B. Schwarz, R. S. Dhaka
https://arxiv.org/abs/2405.05053

Observation of an unconventional giant negative exchange bias effect in La$_{0.5}$Sr$_{0.5}$Co$_{0.85}$Nb$_{0.15}$O$_3$
We find an unconventional giant negative exchange bias (EB) of $H_{\rm EB}$ = --14.1~kOe at 2~K (cooling field of 50~kOe) in the cluster spin-glass (CSG) La$_{0.5}$Sr$_{0.5}$Co$_{0.85}$Nb$_{0.15}$O$_3$ perovsikte cobaltites. The magnetic memory effect, aging measurements, and nonlineraity in specific heat capacity reveal the glassy magnetic state at low temperatures. Further, the detailed analysis of {\it ac-}magnetic susceptibility confirms the glassy state below $\sim$58~K and the obtained ch…

The Simons Observatory: impact of bandpass, polarization angle and calibration uncertainties on small-scale power spectrum analysis
S. Giardiello, M. Gerbino, L. Pagano, D. Alonso, B. Beringue, E. Calabrese, G. Coppi, J. Errard, G. Fabbian, I. Harrison, J. C. Hill, H. T. Jense, B. Keating, A. La Posta, M. Lattanzi, A. I. Lonappan, G. Puglisi, C. L. Reichardt, S. M. Simon

The Simons Observatory: impact of bandpass, polarization angle and calibration uncertainties on small-scale power spectrum analysis
We study the effects due to mismatches in passbands, polarization angles, and temperature and polarization calibrations in the context of the upcoming cosmic microwave background experiment Simons Observatory (SO). Using the SO multi-frequency likelihood, we estimate the bias and the degradation of constraining power in cosmological and astrophysical foreground parameters assuming different levels of knowledge of the instrumental effects. We find that incorrect but reasonable assumptions on the…

Fair Machine Guidance to Enhance Fair Decision Making in Biased People
Mingzhe Yang, Hiromi Arai, Naomi Yamashita, Yukino Baba
https://arxiv.org/abs/2404.05228

Fair Machine Guidance to Enhance Fair Decision Making in Biased People
Teaching unbiased decision-making is crucial for addressing biased decision-making in daily life. Although both raising awareness of personal biases and providing guidance on unbiased decision-making are essential, the latter topics remains under-researched. In this study, we developed and evaluated an AI system aimed at educating individuals on making unbiased decisions using fairness-aware machine learning. In a between-subjects experimental design, 99 participants who were prone to bias perf…

Distributional Reference Class Forecasting of Corporate Sales Growth With Multiple Reference Variables
Etienne Theising
https://arxiv.org/abs/2405.03402 ht…

Distributional Reference Class Forecasting of Corporate Sales Growth With Multiple Reference Variables
This paper introduces an approach to reference class selection in distributional forecasting with an application to corporate sales growth rates using several co-variates as reference variables, that are implicit predictors. The method can be used to detect expert or model-based forecasts exposed to (behavioral) bias or to forecast distributions with reference classes. These are sets of similar entities, here firms, and rank based algorithms for their selection are proposed, including an option…

"The measure would require the regents to set up a department to hear grade challenges based on bias. That department... could determine there was bias and could order the faculty member to regrade the student’s assignment or reevaluate the student’s overall grade." h/t Kevin Reuning @reuning.bsky.social

Students could get grades changed over politics under Arizona Senate plan
Legislation approved by Senate would give university students a new avenue to appeal by alleging "political bias". Teachers could be ordered to change grades.

Observation of in-gap states in a two-dimensional CrI2/NbSe2 heterostructure
Peigen Li, Jihai Zhang, Di Zhu, Cui-Qun Chen, Enkui Yi, Bing Shen, Yusheng Hou, Zhongbo Yan, Dao-Xin Yao, Donghui Guo, Dingyong Zhong
https://arxiv.org/abs/2403.06215

Observation of in-gap states in a two-dimensional CrI2/NbSe2 heterostructure
Low-dimensional magnetic structures coupled with a superconductor are promising platforms for realizing Majorana zero modes, which are considered as novel non-Abelian anyons with potential applications in topological quantum computing. Here, we report the observation of in-gap edge states and zero-bias conductance peaks (ZBCPs) in a two-dimensional (2D) magnetic-superconducting heterostructure consisting of a single-layer chromium diiodide (CrI2) on a niobium diselenide (NbSe2) superconductor. …

A Study of Dropout-Induced Modality Bias on Robustness to Missing Video Frames for Audio-Visual Speech Recognition
Yusheng Dai, Hang Chen, Jun Du, Ruoyu Wang, Shihao Chen, Jiefeng Ma, Haotian Wang, Chin-Hui Lee
https://arxiv.org/abs/2403.04245

A Study of Dropout-Induced Modality Bias on Robustness to Missing Video Frames for Audio-Visual Speech Recognition
Advanced Audio-Visual Speech Recognition (AVSR) systems have been observed to be sensitive to missing video frames, performing even worse than single-modality models. While applying the dropout technique to the video modality enhances robustness to missing frames, it simultaneously results in a performance loss when dealing with complete data input. In this paper, we investigate this contrasting phenomenon from the perspective of modality bias and reveal that an excessive modality bias on the a…

On Bias and Its Reduction via Standardization in Source Localization Problems
Joonas Lahtinen
https://arxiv.org/abs/2405.04409 https://

On Bias and Its Reduction via Standardization in Source Localization Problems
In source localization problems, the aim is to locate the sources within a domain that causes given measurements on the boundary. In this type of problem, biasing of the solution is one of the main causes of mislocalization. A technique called standardization was developed to reduce biasing. However, the lack of a mathematical background for this method can cause difficulties in its application and confusion regarding the reliability of solutions. Here, we give a rigorous and generalized backgr…

Künstliche Intelligenz soll Gender-Klischees in Kinderbüchern aufdecken
Ein KI-Tool soll Gender-Klischees in Kinderbüchern aufdecken, ohne selbst Stereotype zu entwickeln. Ein Score soll über den Gender Bias aufklären.

Robert F Kennedy Jr vows to investigate January 6 prosecutions for political bias (Martin Pengelly/The Guardian)
https://www.theguardian.com/us-news/2024/apr/05/robert-f-kennedy-jr-investigate-january-6-prosecutions
http://www.memeorandum.com/240405/p52#a240405p52

Studies show a negativity bias in US coverage of the economy and gas prices, particularly cable news, as the tone of economic news moves away from reality (John Burn-Murdoch/Financial Times)
https://t.co/Ul22EfLrWv

This https://arxiv.org/abs/2312.13643 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Debiasing Welch's Method for Spectral Density Estimation
Welch's method provides an estimator of the power spectral density that is statistically consistent. This is achieved by averaging over periodograms calculated from overlapping segments of a time series. For a finite length time series, while the variance of the estimator decreases as the number of segments increase, the magnitude of the estimator's bias increases: a bias-variance trade-off ensues when setting the segment number. We address this issue by providing a novel method for debiasing W…

This is not news to some folks.
Bias hiding in plain sight: Decades of analyses suggest US media skews anti-#Palestinian | Salon.com
https://www.

Bias hiding in plain sight: Decades of analyses suggest US media skews anti-Palestinian
Anti-Palestinian bias in the U.S. and other countries’ media is often subtle, albeit in plain view.

Sensing quantum vacuum fluctuations with non-Gaussian electronic noise
Clovis Farley, Edouard Pinsolle, Bertrand Reulet
https://arxiv.org/abs/2404.06594 ht…

Sensing quantum vacuum fluctuations with non-Gaussian electronic noise
The statistics of electron transport in a tunnel junction is affected by fluctuations of its voltage bias, which modulates the probability for electrons to cross the junction. We exploit this phenomenon to provide a direct measurement of quantum vacuum fluctuations in the microwave domain of a resistor placed at ultra-low temperature: we show that the amplified vacuum fluctuations are correlated with the noise generated by the junction to contribute to a third moment of detected voltage fluctua…

Why is the Press Making Trump Seem More Normal?
Yes, a presidential candidate just accused the sitting President of the United States of delivering the State of the Union address while high on cocaine.

I’m guessing that unless you listened to the Friday episode of Pod Save America, most of you are learning this information for the first time.
And it's not because you aren’t avid consumers of news. It’s because the traditional political media decided to ignore thi…

Why is the Press Making Trump Seem More Normal?
Believe it or not, much of the political press has an inadvertent pro-Trump bias

Validating the Galaxy and Quasar Catalog-Level Blinding Scheme for the DESI 2024 analysis
U. Andrade, J. Mena-Fern\'andez, H. Awan, A. J. Ross, S. Brieden, J. Pan, A. de Mattia, J. Aguilar, S. Ahlen, O. Alves, D. Brooks, E. Buckley-Geer, E. Chaussidon, T. Claybaugh, S. Cole, A. de la Macorra, Arjun Dey, P. Doel, K. Fanning, J. E. Forero-Romero, E. Gazta\~naga, H. Gil-Mar\'in, S. Gontcho A Gontcho, J. Guy, C. Hahn, M. M. S Hanif, K. Honscheid, C. Howlett, D. Huterer, S. Juneau, …

Validating the Galaxy and Quasar Catalog-Level Blinding Scheme for the DESI 2024 analysis
In the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount -- a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the data volume and the impact of the findings, the potential for confirmation bias poses a significant challenge. To address this, we implement…

The Power of Absence: Thinking with Archival Theory in Algorithmic Design
Jihan Sherman, Romi Morrison, Lauren Klein, Daniela K. Rosner
https://arxiv.org/abs/2405.05420

The Power of Absence: Thinking with Archival Theory in Algorithmic Design
This paper explores the value of archival theory as a means of grappling with bias in algorithmic design. Rather than seek to mitigate biases perpetuated by datasets and algorithmic systems, archival theory offers a reframing of bias itself. Drawing on a range of archival theory from the fields of history, literary and cultural studies, Black studies, and feminist STS, we propose absence-as power, presence, and productive-as a concept that might more securely anchor investigations into the caus…

This https://arxiv.org/abs/2201.13451 has been replaced.
link: https://scholar.google.com/scholar?q=a

Nonlinear Regression with Residuals: Causal Estimation with Time-varying Treatments and Covariates
Standard regression adjustment gives inconsistent estimates of causal effects when there are time-varying treatment effects and time-varying covariates. Loosely speaking, the issue is that some covariates are post-treatment variables because they may be affected by prior treatment status, and regressing out post-treatment variables causes bias. More precisely, the bias is due to certain non-confounding latent variables that create colliders in the causal graph. These latent variables, which we …

BiasKG: Adversarial Knowledge Graphs to Induce Bias in Large Language Models
Chu Fei Luo, Ahmad Ghawanmeh, Xiaodan Zhu, Faiza Khan Khattak
https://arxiv.org/abs/2405.04756

BiasKG: Adversarial Knowledge Graphs to Induce Bias in Large Language Models
Modern large language models (LLMs) have a significant amount of world knowledge, which enables strong performance in commonsense reasoning and knowledge-intensive tasks when harnessed properly. The language model can also learn social biases, which has a significant potential for societal harm. There have been many mitigation strategies proposed for LLM safety, but it is unclear how effective they are for eliminating social biases. In this work, we propose a new methodology for attacking langu…

NPR CEO Katherine Maher will not attend a US House committee hearing on May 8 looking at alleged NPR bias due to a schedule conflict, but offers to appear later (Austin Fuller/Current)
https://current.org/2024/05/npr-ceo-wont-attend-house-hear…

NPR CEO won’t attend House hearing on allegations of bias
A meeting of NPR’s board of directors, Maher's first since joining the network, was scheduled for Wednesday more than a year ahead of time.

How bills under consideration in various US states to address AI bias contain loopholes that would make companies avoiding accountability easier (Politico)
https://www.politico.com/news/magazine/2024/04/30/ai-legislation-states-mistake-0015…

Bias in Generative AI
Mi Zhou, Vibhanshu Abhishek, Timothy Derdenger, Jaymo Kim, Kannan Srinivasan
https://arxiv.org/abs/2403.02726 https://

Bias in Generative AI
This study analyzed images generated by three popular generative artificial intelligence (AI) tools - Midjourney, Stable Diffusion, and DALLE 2 - representing various occupations to investigate potential bias in AI generators. Our analysis revealed two overarching areas of concern in these AI generators, including (1) systematic gender and racial biases, and (2) subtle biases in facial expressions and appearances. Firstly, we found that all three AI generators exhibited bias against women and A…

2024 NFL mock draft ... with a twist! What every team SHOULD do in Round 1 https://www.nfl.com/news/2024-nfl-mock-draft-with-a-twist-what-every-team-should-do-in-round-1

2024 NFL mock draft ... with a twist! What every team SHOULD do in Round 1
There's no shortage of 2024 NFL mock drafts exploring what each team COULD do, but how about what everyone SHOULD do? Adam Rank simulates the first round with full bias. Check out all of his picks, 1-32.

A3COSMOS & A3GOODSS: Continuum Source Catalogues and Multi-band Number Counts
Sylvia Adscheid, Benjamin Magnelli, Daizhong Liu, Frank Bertoldi, Ivan Delvecchio, Carlotta Gruppioni, Eva Schinnerer, Alberto Traina, Matthieu B\'ethermin, Athanasia Gkogkou
https://arxiv.org/abs/2403.03125 https://arxiv.org/pdf/2403.03125
arXiv:2403.03125v1 Announce Type: new
Abstract: Galaxy submillimetre number counts are a fundamental measurement in our understanding of galaxy evolution models. Most early measurements are obtained via single-dish telescopes with substantial source confusion, whereas recent interferometric observations are limited to small areas. We used a large database of ALMA continuum observations to accurately measure galaxy number counts in multiple (sub)millimetre bands, thus bridging the flux density range between single-dish surveys and deep interferometric studies. We continued the Automated Mining of the ALMA Archive in the COSMOS Field project (A3COSMOS) and extended it with observations from the GOODS-South field (A3GOODSS). The database consists of ~4,000 pipeline-processed continuum images from the public ALMA archive, yielding 2,050 unique detected sources. To infer galaxy number counts, we constructed a method to reduce the observational bias inherent to targeted pointings that dominate the database. This method comprises a combination of image selection, masking, and source weighting. The effective area was calculated by accounting for inhomogeneous wavelengths, sensitivities, and resolutions and for spatial overlap between images. We tested and calibrated our method with simulations. We obtained the first number counts derived in a consistent and homogeneous way in four different ALMA bands covering a relatively large area. The results are consistent with number counts from the literature within the uncertainties. We extended the available depth in ALMA Band 4 by 0.4 dex with respect to previous studies. In Band 7, at the depth of the inferred number counts, ~40% of the cosmic infrared background is resolved into discrete sources. This fraction, however, decreases with wavelength, reaching ~4% in Band 3. Finally, we used the number counts to test models of dusty galaxy evolution, and find a good agreement within the uncertainties.

This https://arxiv.org/abs/2305.03479 has been replaced.
initial toot: https://mastoxiv.page/@a…

Pauli blockade catalogue and three- and four-particle Kondo effect in bilayer graphene quantum dots
Pauli blockade is a fundamental quantum phenomenon that also serves as a powerful tool for qubit manipulation and read-out. While most systems exhibit a simple even-odd pattern of double-dot Pauli spin blockade due to the preferred singlet pairing of spins, the additional valley degree of freedom offered by bilayer graphene greatly alters this pattern. Inspecting bias-triangle measurements at double-dot charge degeneracies with up to four electrons in each dot reveals a much richer double-dot P…

BiasKG: Adversarial Knowledge Graphs to Induce Bias in Large Language Models
Chu Fei Luo, Ahmad Ghawanmeh, Xiaodan Zhu, Faiza Khan Khattak
https://arxiv.org/abs/2405.04756

BiasKG: Adversarial Knowledge Graphs to Induce Bias in Large Language Models
Modern large language models (LLMs) have a significant amount of world knowledge, which enables strong performance in commonsense reasoning and knowledge-intensive tasks when harnessed properly. The language model can also learn social biases, which has a significant potential for societal harm. There have been many mitigation strategies proposed for LLM safety, but it is unclear how effective they are for eliminating social biases. In this work, we propose a new methodology for attacking langu…

A General Identification Algorithm For Data Fusion Problems Under Systematic Selection
Jaron J. R. Lee, AmirEmad Ghassami, Ilya Shpitser
https://arxiv.org/abs/2404.06602

A General Identification Algorithm For Data Fusion Problems Under Systematic Selection
Causal inference is made challenging by confounding, selection bias, and other complications. A common approach to addressing these difficulties is the inclusion of auxiliary data on the superpopulation of interest. Such data may measure a different set of variables, or be obtained under different experimental conditions than the primary dataset. Analysis based on multiple datasets must carefully account for similarities between datasets, while appropriately accounting for differences. In add…

Pitfalls of Conversational LLMs on News Debiasing
Ipek Baris Schlicht, Defne Altiok, Maryanne Taouk, Lucie Flek
https://arxiv.org/abs/2404.06488 https://…

Pitfalls of Conversational LLMs on News Debiasing
This paper addresses debiasing in news editing and evaluates the effectiveness of conversational Large Language Models in this task. We designed an evaluation checklist tailored to news editors' perspectives, obtained generated texts from three popular conversational models using a subset of a publicly available dataset in media bias, and evaluated the texts according to the designed checklist. Furthermore, we examined the models as evaluator for checking the quality of debiased model outputs. …

Causal Disentanglement for Regulating Social Influence Bias in Social Recommendation
Li Wang, Min Xu, Quangui Zhang, Yunxiao Shi, Qiang Wu
https://arxiv.org/abs/2403.03578

Causal Disentanglement for Regulating Social Influence Bias in Social Recommendation
Social recommendation systems face the problem of social influence bias, which can lead to an overemphasis on recommending items that friends have interacted with. Addressing this problem is crucial, and existing methods often rely on techniques such as weight adjustment or leveraging unbiased data to eliminate this bias. However, we argue that not all biases are detrimental, i.e., some items recommended by friends may align with the user's interests. Blindly eliminating such biases could under…

“I want to be clear,” Move On's Epting said.
“Robert Kennedy Jr’s ill-fated run for the presidency is helping put Donald Trump back in the White House and we’re going to work to stop that.
Just as we organised against No Labels we’re going to organise against Robert Kennedy Jr. We’re going to let folks know we can’t win, but he can help Trump win.”

Sources: Gemini's image generation tool had a technical fix to reduce bias in its outputs but Google didn't anticipate the overcorrection and wasn't transparent (Bloomberg)
https://www.bloomberg.com/news/articles/20

Google Left in ‘Terrible Bind’ By Pulling AI Feature After Right-Wing Backlash
Google tried using a technical fix to reduce bias in a feature that generates realistic-looking images of people. Instead, it set off a new diversity firestorm.

This https://arxiv.org/abs/2305.13835 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Methodological refinement of the submillimeter galaxy magnification bias. I. Cosmological analysis with a single redshift bin
The main goal of this work, the second in a three-paper series, is to test the impact of a methodological improvement in measuring the magnification bias signal on a sample of submillimeter galaxies and its implications for constraining cosmological parameters. The analysis considers the angular cross-correlation function between a foreground sample of GAMA galaxies ($0.2

Regularized Principal Spline Functions to Mitigate Spatial Confounding
Carlo Zaccardi, Pasquale Valentini, Luigi Ippoliti, Alexandra M. Schmidt
https://arxiv.org/abs/2403.05373

Regularized Principal Spline Functions to Mitigate Spatial Confounding
This paper proposes a new approach to address the problem of unmeasured confounding in spatial designs. Spatial confounding occurs when some confounding variables are unobserved and not included in the model, leading to distorted inferential results about the effect of an exposure on an outcome. We show the relationship existing between the confounding bias of a non-spatial model and that of a semi-parametric model that includes a basis matrix to represent the unmeasured confounder conditional …

Quantum Hall interferometry at finite bias with multiple edge channels
Zezhu Wei, D. E. Feldman, Bertrand I. Halperin
https://arxiv.org/abs/2405.05486 http…

Quantum Hall interferometry at finite bias with multiple edge channels
In a quantum Hall interferometer, the dependence of the signal on source-drain voltage is controlled by details of the edge physics, such as the velocities of edge modes and the interaction between them and with screening layers. Such dependence of the signal has been seen in recent experiments at various integer and fractional filling factors, including $ν=2$ and $ν=2/5$ where two edge modes are present. Here we study theoretically the current-voltage curves for various values of the relativ…

This https://arxiv.org/abs/2309.13933 has been replaced.
link: https://scholar.google.com/scholar?q=a

Fairness and Bias in Algorithmic Hiring: a Multidisciplinary Survey
Employers are adopting algorithmic hiring technology throughout the recruitment pipeline. Algorithmic fairness is especially applicable in this domain due to its high stakes and structural inequalities. Unfortunately, most work in this space provides partial treatment, often constrained by two competing narratives, optimistically focused on replacing biased recruiter decisions or pessimistically pointing to the automation of discrimination. Whether, and more importantly what types of, algorithm…

Probabilistic Lagrangian bias estimators and the cumulant bias expansion
Jens St\"ucker, Marcos Pellejero-Ib\'a\~nez, Raul E. Angulo, Francisco Maion, Rodrigo Voivodic
https://arxiv.org/abs/2405.01950

Probabilistic Lagrangian bias estimators and the cumulant bias expansion
The spatial distribution of galaxies is a highly complex phenomenon currently impossible to predict deterministically. However, by using a statistical $\textit{bias}$ relation, it becomes possible to robustly model the average abundance of galaxies as a function of the underlying matter density field. Understanding the properties and parametric description of the bias relation is key to extract cosmological information from future galaxy surveys. Here, we contribute to this topic primarily in t…

This https://arxiv.org/abs/2405.00238 has been replaced.
initial toot: https://mastoxiv.page/@a…

Noise reduction by bias cooling in gated Si/SixGe1-x qunatum dots
Silicon-Germanium heterostructures are a promising quantum circuit platform, but crucial aspects as the long-term charge dynamics and cooldown-to-cooldown variations are still widely unexplored quantitatively. In this letter we present the results of an extensive bias cooling study performed on gated silicon-germanium quantum dots with an Al2O3-dielectric. Over 80 cooldowns were performed in the course of our investigations. The performance of the devices is assessed by low-frequency charge noi…

Gender Bias in Large Language Models across Multiple Languages
Jinman Zhao, Yitian Ding, Chen Jia, Yining Wang, Zifan Qian
https://arxiv.org/abs/2403.00277

Gender Bias in Large Language Models across Multiple Languages
With the growing deployment of large language models (LLMs) across various applications, assessing the influence of gender biases embedded in LLMs becomes crucial. The topic of gender bias within the realm of natural language processing (NLP) has gained considerable focus, particularly in the context of English. Nonetheless, the investigation of gender bias in languages other than English is still relatively under-explored and insufficiently analyzed. In this work, We examine gender bias in LLM…

This https://arxiv.org/abs/2305.13834 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Methodological refinement of the submillimeter galaxy magnification bias. Paper 0: cross-correlation function measurements
The measurement of the cross-correlation function is crucial to assess magnification bias in galaxy surveys. Previous works used mini-tile subsampling, but accurately determining the integral constraint (IC) correction for unbiased estimation is challenging due to various factors. We present a new methodology for estimating the cross-correlation function, utilizing full field area and reducing statistical uncertainty. Covariance matrices were estimated by dividing each field into at least five …

Three House Republicans call on NPR CEO Katherine Maher to appear at a hearing on May 8 following ex-staffer Uri Berliner's allegations of bias in news coverage (Ted Johnson/Deadline)
https://deadline.com/2024/05/npr-ceo-house-republicans-inves…

House Republicans Ask NPR CEO To Appear At Hearing After Bias Allegations
A former business editor accused the network of lacking viewpoint diversity.

Gaussian Lagrangian Galaxy Bias
Jens St\"ucker, Marcos Pellejero-Ib\'a\~nez, Rodrigo Voivodic, Raul E. Angulo
https://arxiv.org/abs/2405.01951 htt…

Gaussian Lagrangian Galaxy Bias
Understanding $\textit{galaxy bias}$ -- that is the statistical relation between matter and galaxies -- is of key importance for extracting cosmological information from galaxy surveys. While the bias function $f$ is usually approximated through a parametric expansion, we show here, that it can also be measured directly from simulations in a non-parameteric way. Our measurements show that the Lagrangian bias function is very close to a Gaussian for halo selections of any mass. Therefore, we new…

This https://arxiv.org/abs/2402.01740 has been replaced.
link: https://scholar.google.com/scholar?q=a

Compensatory Biases Under Cognitive Load: Reducing Selection Bias in Large Language Models
Large Language Models (LLMs) like gpt-3.5-turbo and claude-instant-1.2 have become instrumental in interpreting and executing semantic-based tasks. Unfortunately, these models' inherent biases, akin to human cognitive biases, adversely affect their performance. Particularly affected is object selection from lists; a fundamental operation in digital navigation and decision-making. This research critically examines these biases and quantifies the effects on a representative list selection task. T…

Cosmic Insights from Galaxy Clusters: Exploring Magnification Bias on Sub-millimeter Galaxies
Rebeca Fern\'andez-Fern\'andez, Laura Bonavera, David Crespo, Joaqu\'in Gonz\'alez-Nuevo, Marcos M. Cueli, Jos\'e Manuel Casas, Sara R. Cabo
https://arxiv.org/abs/2403.03855 …

Cosmic Insights from Galaxy Clusters: Exploring Magnification Bias on Sub-millimeter Galaxies
Magnification bias, an observational effect of gravitational lensing in the weak regime, allows testing the cosmological model through angular correlations of sources at different redshifts. This effect has been observed in various contexts, particularly with sub-millimeter galaxies (SMGs), offering astrophysical and cosmological insights. The study aims to investigate the magnification bias effect exerted by galaxy clusters on SMGs and its implications for astrophysical and cosmological parame…