Tootfinder

Top Cowboys rookie credits veterans for helping grow technique, confidence https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/08/22/tyler-booker-highlights-confidence-and-veteran-help-…

Confidence-gated training for efficient early-exit neural networks
Saad Mokssit, Ouassim Karrakchou, Alejandro Mousist, Mounir Ghogho
https://arxiv.org/abs/2509.17885 https://…

Confidence-gated training for efficient early-exit neural networks
Early-exit neural networks reduce inference cost by enabling confident predictions at intermediate layers. However, joint training often leads to gradient interference, with deeper classifiers dominating optimization. We propose Confidence-Gated Training (CGT), a paradigm that conditionally propagates gradients from deeper exits only when preceding exits fail. This encourages shallow classifiers to act as primary decision points while reserving deeper layers for harder inputs. By aligning train…

Confidence-Modulated Speculative Decoding for Large Language Models
Jaydip Sen, Subhasis Dasgupta, Hetvi Waghela
https://arxiv.org/abs/2508.15371 https://a…

Confidence-Modulated Speculative Decoding for Large Language Models
Speculative decoding has emerged as an effective approach for accelerating autoregressive inference by parallelizing token generation through a draft-then-verify paradigm. However, existing methods rely on static drafting lengths and rigid verification criteria, limiting their adaptability across varying model uncertainties and input complexities. This paper proposes an information-theoretic framework for speculative decoding based on confidence-modulated drafting. By leveraging entropy and mar…

Lions' unsung defense steps up, surprises even Dan Campbell: 'I had confidence, but nine points?' https://www.nfl.com/news/lions-unsung-defense-steps-up-surprises-even-dan-campbell-i-had-confidence-but-nine-points

Sonos names interim CEO Tom Conrad as CEO, effective immediately, as it works to restore confidence after its app disaster; Conrad took the job in January 2025 (Chris Welch/Bloomberg)
https://www.bloomberg.com/news/articles/20

Improving U-Net Confidence on TEM Image Data with L2-Regularization, Transfer Learning, and Deep Fine-Tuning
Aiden Ochoa, Xinyuan Xu, Xing Wang
https://arxiv.org/abs/2507.16779

Improving U-Net Confidence on TEM Image Data with L2-Regularization, Transfer Learning, and Deep Fine-Tuning
With ever-increasing data volumes, it is essential to develop automated approaches for identifying nanoscale defects in transmission electron microscopy (TEM) images. However, compared to features in conventional photographs, nanoscale defects in TEM images exhibit far greater variation due to the complex contrast mechanisms and intricate defect structures. These challenges often result in much less labeled data and higher rates of annotation errors, posing significant obstacles to improving ma…

Raiders' Greg Olson Has Surprising Source for Geno Smith Confidence https://www.si.com/nfl/raiders/las-vegas-pete-carroll-greg-olson-geno-smith

Can we have it all? Non-asymptotically valid and asymptotically exact confidence intervals for expectations and linear regressions
Alexis Derumigny, Lucas Girard, Yannick Guyonvarch
https://arxiv.org/abs/2507.16776

Can we have it all? Non-asymptotically valid and asymptotically exact confidence intervals for expectations and linear regressions
We contribute to bridging the gap between large- and finite-sample inference by studying confidence sets (CSs) that are both non-asymptotically valid and asymptotically exact uniformly (NAVAE) over semi-parametric statistical models. NAVAE CSs are not easily obtained; for instance, we show they do not exist over the set of Bernoulli distributions. We first derive a generic sufficient condition: NAVAE CSs are available as soon as uniform asymptotically exact CSs are. Second, building on that con…

Comment on Frank Porter, "Confidence intervals for the Poisson distribution"
Robert D. Cousins
https://arxiv.org/abs/2509.17339 https://arxiv.org…

Comment on Frank Porter, "Confidence intervals for the Poisson distribution"
Frank Porter has recently posted a review of "Confidence intervals for the Poisson distribution" (arXiv:2509.02852). The long, diverse history of such intervals is closely related to that of confidence intervals for the parameter of the binomial distribution. While much of Porter's paper is enlightening and food for thought, I believe that his discussion of the intervals advocated by Gary Feldman and myself (FC) based on the likelihood ratio test (arXiv:physics/9711021) is flawed. The fundament…

Cross-Attention with Confidence Weighting for Multi-Channel Audio Alignment
Ragib Amin Nihal, Benjamin Yen, Takeshi Ashizawa, Kazuhiro Nakadai
https://arxiv.org/abs/2509.16926 h…

Cross-Attention with Confidence Weighting for Multi-Channel Audio Alignment
Multi-channel audio alignment is a key requirement in bioacoustic monitoring, spatial audio systems, and acoustic localization. However, existing methods often struggle to address nonlinear clock drift and lack mechanisms for quantifying uncertainty. Traditional methods like Cross-correlation and Dynamic Time Warping assume simple drift patterns and provide no reliability measures. Meanwhile, recent deep learning models typically treat alignment as a binary classification task, overlooking inte…

@… I get the nickname part. I call it Charlie Gupta. You know, the guy in the pub who knows everything, and has an opinion on everything and will tell it to you, with all the confidence in the world. Accuracy is not his strength.

Data-Driven Probabilistic Evaluation of Logic Properties with PAC-Confidence on Mealy Machines
Swantje Plambeck, Ali Salamati, Eyke Huellermeier, Goerschwin Fey
https://arxiv.org/abs/2508.14710

Data-Driven Probabilistic Evaluation of Logic Properties with PAC-Confidence on Mealy Machines
Cyber-Physical Systems (CPS) are complex systems that require powerful models for tasks like verification, diagnosis, or debugging. Often, suitable models are not available and manual extraction is difficult. Data-driven approaches then provide a solution to, e.g., diagnosis tasks and verification problems based on data collected from the system. In this paper, we consider CPS with a discrete abstraction in the form of a Mealy machine. We propose a data-driven approach to determine the safety p…

Confidence Estimation for Text-to-SQL in Large Language Models
Sepideh Entezari Maleki, Mohammadreza Pourreza, Davood Rafiei
https://arxiv.org/abs/2508.14056 https://

Confidence Estimation for Text-to-SQL in Large Language Models
Confidence estimation for text-to-SQL aims to assess the reliability of model-generated SQL queries without having access to gold answers. We study this problem in the context of large language models (LLMs), where access to model weights and gradients is often constrained. We explore both black-box and white-box confidence estimation strategies, evaluating their effectiveness on cross-domain text-to-SQL benchmarks. Our evaluation highlights the superior performance of consistency-based methods…

FROQ: Observing Face Recognition Models for Efficient Quality Assessment
\v{Z}iga Babnik, Deepak Kumar Jain, Peter Peer, Vitomir \v{S}truc
https://arxiv.org/abs/2509.17689 https…

FROQ: Observing Face Recognition Models for Efficient Quality Assessment
Face Recognition (FR) plays a crucial role in many critical (high-stakes) applications, where errors in the recognition process can lead to serious consequences. Face Image Quality Assessment (FIQA) techniques enhance FR systems by providing quality estimates of face samples, enabling the systems to discard samples that are unsuitable for reliable recognition or lead to low-confidence recognition decisions. Most state-of-the-art FIQA techniques rely on extensive supervised training to achieve a…

Surfacing from replies (see context upthread).
I’ve watched the pendulum swing back and forth multiple times in my career between “code reuse ftw!!” and “no dependencies!!” The one thing I can say with confidence is that both those extremes as dogma are ridiculous and costly. It’s all tradeoffs; you can’t escape the part where you think carefully and contextually.
1/ https://hachyderm.io/@inthehands/115237696859291899

Dak Prescott Turns 'Sky-High' Confidence Into LFG Player of the Game Performance https://www.foxsports.com/stories/nfl/dak-prescott-turns-sky-high-confidence-lfg-player-game-mvp-campaign

Agatha Christie im Jahr 1973:

Depth, Confidence, Competition: Raiders’ Young Core Brings Fresh Hope https://raiderramble.com/2025/08/20/depth-confidence-competition-raiders-young-core-brings-fresh-hope/

CARGO: A Framework for Confidence-Aware Routing of Large Language Models
Amine Barrak, Yosr Fourati, Michael Olchawa, Emna Ksontini, Khalil Zoghlami
https://arxiv.org/abs/2509.14899

CARGO: A Framework for Confidence-Aware Routing of Large Language Models
As large language models (LLMs) proliferate in scale, specialization, and latency profiles, the challenge of routing user prompts to the most appropriate model has become increasingly critical for balancing performance and cost. We introduce CARGO (Category-Aware Routing with Gap-based Optimization), a lightweight, confidence-aware framework for dynamic LLM selection. CARGO employs a single embedding-based regressor trained on LLM-judged pairwise comparisons to predict model performance, with a…

A $6.37\,{\rm Hz}$ quasi-periodic oscillating photospheric emission in GRB~240825A
Guo-Yu Li, Da-Bin Lin, Zhi-Lin Chen, Bao-Quan Huang, Tong Liu, En-Wei Liang
https://arxiv.org/abs/2507.16538

A $6.37\,{\rm Hz}$ quasi-periodic oscillating photospheric emission in GRB~240825A
Using data from Swift-BAT and Fermi-GBM, we report the first detection of a high-confidence quasi-periodic oscillation (QPO) in the thermal emission of gamma-ray burst GRB~240825A. The spectral analysis of the burst reveals two radiation components, including a thermal emission dominant in $100 \text{--} 300\,\mathrm{keV}$ and a non-thermal emission spanning a wide energy range. During the interval $2.07 \text{--} 3.25\,\mathrm{s}$ post-trigger, a strong QPO signal at $6.37\,\mathrm{Hz}$ ($\gtr…

Is there a moth identification expert out there? Spotted this beauty (sorry for blurry photos) at weekend on SamsŸ. Arter suggests Spilosoma urticae (hvid tiger spinder/ water ermine) but low confidence. I don't see fluffy white antennae on that one though. Any other suggestions? #hiveMind
EDIT: update, I think we have identified it as Euproctis Similis which may or may not be the same species as Sphrageidus similis. Known as Gulhale in Danish and Yellow-tail in English
https://en.m.wikipedia.org/wiki/Yellow-tail
https://www.naturbasen.dk/art/874/gulhale

Many parts of the Internet I know and loath are mostly down. I hope this helps shake confidence in US BigTech. Probably won't, because if people were rational, they wouldn't have built the digital world we're currently forced to inhabit, but who knows, it might. Even the vague possibility of it has made my day better as I head to bed.

One day till we talk about FAPI 2.0 here at #Duende. If you're interested in the latest and greatest in security specifications for your #aspnetcore apps, then you'll want to register and join us.

Likelihood confidence intervals for misspecified Cox models
Yongwu Shao, Xu Guo
https://arxiv.org/abs/2508.11851 https://arxiv.org/pdf/2508.11851

Likelihood confidence intervals for misspecified Cox models
The robust Wald confidence interval (CI) for the Cox model is commonly used when the model may be misspecified or when weights are applied. However it can perform poorly when there are few events in one or both treatment groups, as may occur when the event of interest is rare or when the experimental arm is highly efficacious. For instance, if we artificially remove events (assuming more events are unfavorable) from the experimental group, the resulting upper CI may increase. This is clearly co…

JWST-TST DREAMS: Sulfur dioxide in the atmosphere of the Neptune-mass planet HAT-P-26 b from NIRSpec G395H transmission spectroscopy
Am\'elie Gressier, Natasha E. Batalha, Nicholas Wogan, Lili Alderson, Dominic Doud, N\'estor Espinoza, Ryan J. MacDonald, Hannah R. Wakeford, Jeff A. Valenti, Nikole K. Lewis, Sara Seager, Kevin B. Stevenson, Natalie H. Allen, Caleb I. Ca\~nas, Ryan C. Challener, Ana Glidden, Jingcheng Huang, Zifan Lin, Dana R. Louie, Cathal Maguire, Elijah Mullen…

JWST-TST DREAMS: Sulfur dioxide in the atmosphere of the Neptune-mass planet HAT-P-26 b from NIRSpec G395H transmission spectroscopy
We present the James Webb Space Telescope (JWST) transmission spectrum of the exoplanet HAT-P-26 b (18.6 Earth masses, 6.33 Earth radii), based on a single transit observed with the JWST NIRSpec G395H grating. We detect water vapor (ln B = 4.1), carbon dioxide (ln B = 85.6), and sulfur dioxide (ln B = 13.5) with high confidence, along with marginal indications for hydrogen sulfide and carbon monoxide (ln B < 0.5). The detection of SO2 in a warm super-Neptune sized exoplanet (radius about 6 Eart…

Modeling Scintillation Photon Transport and Reconstruction Algorithms for the Time-of-Flight Detector in the T2K Neutrino Experiment
C. Alt, A. Blanchet, S. Bordoni, P. Collard, T. H. Bui, M. H. Bui, G. Ha, C. Jes\'us-Valls, V. S. Kasturi, A. Klustov\'a, A. Korzenev, T. A. Le, T. Lux, A. D. Nguyen, D. T. Nguyen, H. Nguyen, S. Samani, F. S\'anchez, M. Ta, T. Tha\'iduc, E. Villa

Modeling Scintillation Photon Transport and Reconstruction Algorithms for the Time-of-Flight Detector in the T2K Neutrino Experiment
The T2K ND280 upgrade aims to reduce the systematic uncertainty of the CP-violating phase, $δ_{CP}$, to reject non-CP violation hypothesis at $3σ$ confidence level. A crucial component of the ND280 upgrade, alongside the Super Fine Grained Detector (SuperFGD) and two High-Angle Time Projection Chambers (TPCs), is the Time-of-Flight (ToF) detector, which significantly enhances background rejection and particle identification capabilities. The ToF detector features six modules in a cube configu…

Examining Gender Differences in the Impact of Instructional Clarity on Year 9 Students' Mathematics Interest in New Zealand: A Multi-Group Comparison of 2019 TIMSS Data
Huayu Gao, Tanya Evans, Gavin T. L. Brown
https://arxiv.org/abs/2508.13502

Examining Gender Differences in the Impact of Instructional Clarity on Year 9 Students' Mathematics Interest in New Zealand: A Multi-Group Comparison of 2019 TIMSS Data
Grounded in Social Cognitive Career Theory (SCCT), this study explores how teacher instruction clarity impacts Year 9 students' mathematics interest through the mediating roles of confidence and value, with a focus on gender differences. Structural equation modelling applied to the 2019 New Zealand TIMSS dataset (2,594 girls and 2,651 boys) supports the SCCT framework. While confidence and value have similar mediating effects for boys, confidence plays a more pivotal role for girls. Gender diff…

Week 4 NFL Power Rankings: 49ers, Bears rise as injuries take their toll on QBs https://www.nytimes.com/athletic/6652493/2025/09/23/nfl-power-rankings-week-4-caleb-williams-bears-49ers/

Designing Tools with Control Confidence
Ajith Anil Meera, Abian Torres, Pablo Lanillos
https://arxiv.org/abs/2510.12630 https://arxiv.org/pdf/2510.12630

Designing Tools with Control Confidence
Prehistoric humans invented stone tools for specialized tasks by not just maximizing the tool's immediate goal-completion accuracy, but also increasing their confidence in the tool for later use under similar settings. This factor contributed to the increased robustness of the tool, i.e., the least performance deviations under environmental uncertainties. However, the current autonomous tool design frameworks solely rely on performance optimization, without considering the agent's confidence in…

I don’t even know what to say about Salah. Bereft of confidence.
Even Gakpo would have hit the woodwork…
#LFC

A comparison between behavioral similarity methods vs standard deviation method in predicting time series dataset, case study of finance market
Mahdi Goldani
https://arxiv.org/abs/2507.16655

A comparison between behavioral similarity methods vs standard deviation method in predicting time series dataset, case study of finance market
In statistical modeling, prediction and explanation are two fundamental objectives. When the primary goal is forecasting, it is important to account for the inherent uncertainty associated with estimating unknown outcomes. Traditionally, confidence intervals constructed using standard deviations have served as a formal means to quantify this uncertainty and evaluate the closeness of predicted values to their true counterparts. This approach reflects an implicit aim to capture the behavioral sim…

🗷 Gerrymandering erodes confidence in democracy
#politics

Gerrymandering erodes confidence in democracy
When politicians redraw congressional district maps to favor their party, they may secure short-term victories. But those wins can come at a steep price—a loss of public faith in elections and, ultimately, in democracy itself.

Poll finds low public confidence in federal vaccine policy changes:
https://www.cidrap.umn.edu/childhood-vaccines/poll-finds-low-public-confidence-federal-vaccine-policy-changes

Breakable Machine: A K-12 Classroom Game for Transformative AI Literacy Through Spoofing and eXplainable AI (XAI)
Olli Hilke, Nicolas Pope, Juho Kahila, Henriikka Vartiainen, Teemu Roos, Tuomo Parkki, Matti Tedre
https://arxiv.org/abs/2508.14201

Breakable Machine: A K-12 Classroom Game for Transformative AI Literacy Through Spoofing and eXplainable AI (XAI)
This paper, submitted to the special track on resources for teaching AI in K-12, presents an eXplainable AI (XAI)-based classroom game "Breakable Machine" for teaching critical, transformative AI literacy through adversarial play and interrogation of AI systems. Designed for learners aged 10-15, the game invites students to spoof an image classifier by manipulating their appearance or environment in order to trigger high-confidence misclassifications. Rather than focusing on building AI models,…

A statement from iNaturalist on experimenting with “AI-Assisted Identification Summaries” in 'Exploring New Ways to Learn from iNaturalist’s Community Expertise' https://www.inaturalist.org/blog/118695-exploring-new-ways…

Crosslisted article(s) found for cs.DB. https://arxiv.org/list/cs.DB/new
[1/1]:
- Confidence Estimation for Text-to-SQL in Large Language Models
Sepideh Entezari Maleki, Mohammadreza Pourreza, Davood Rafiei

NFL Week 7 confidence picks: Cowboys, Colts, Vikings among upset picks https://www.nytimes.com/athletic/6718596/2025/10/15/nfl-week-7-confidence-picks-cowboys-colts-vikings-upsets-betting/

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[3/5]:
- Calibrating LLM Confidence by Probing Perturbed Representation Stability
Khanmohammadi, Miahi, Mardikoraem, Kaur, Brugere, Smiley, Thind, Ghassemi

Far right and far left in EU Parliament to file separate von der Leyen no-confidence motions at midnight (Max Griera/Politico)
https://www.politico.eu/article/far-right-far-left-eu-parliament-von-der-leyen-no-confidence-motion-midnight/
http://www.memeorandum.com/250910/p30#a250910p30

Ouste! (Yes it's a French word)
"French prime minister to face potential ousting in high-stakes confidence vote"
https://www.theguardian.com/world/2025/aug/25/francois-bayrou-france-prime-minister-confidence-vote

Cowboys Players Having ‘Doubts’ After Brutal Start From Defense https://heavy.com/sports/nfl/dallas-cowboys/doubts-after-brutal-start-defense/?adt_ei=[email]

Lightweight and Accurate Multi-View Stereo with Confidence-Aware Diffusion Model
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys
https://arxiv.org/abs/2509.15220 http…

Lightweight and Accurate Multi-View Stereo with Confidence-Aware Diffusion Model
To reconstruct the 3D geometry from calibrated images, learning-based multi-view stereo (MVS) methods typically perform multi-view depth estimation and then fuse depth maps into a mesh or point cloud. To improve the computational efficiency, many methods initialize a coarse depth map and then gradually refine it in higher resolutions. Recently, diffusion models achieve great success in generation tasks. Starting from a random noise, diffusion models gradually recover the sample with an iterativ…

"The US is the richest country in the world!"
Oh yeah? What does its balance sheet look like?
Obviously it's absurd to ask that question, as any economist will happily explain why national debts shouldn't be treated like real money.
But it's also absurd that it's absurd to ask that question, and there's a thread to pull here: is the US "rich" because many billionaires live here? That doesn't seem to improve the lives of most of the population. Is it because our median income is so much larger than many other countries? That's in large part a product of exchange rates, since costs of living are also higher here, so is the real reason the fact that the dollar has so much purchasing power? Why does it?
Well, at some level of abstraction, exchange rates boil down to: "How much confidence do the ultra-rich place in the stability of the country" which is intimately related to: "How much military/diplomatic power does the country have?"
So... The US is the "richest" country in the world because it uses its military dominance to bully other countries and keep them down, and it also uses the resulting economic dominance to do the same. We can see this happening via US-sponsored coups, International Monetary Fund bullying, and attendant multinational corporate looting of countries with little economic power (rampant in Africa and Central America, for example).

Asymptotic confidence bands for the histogram regression estimator
Natalie Neumeyer, Jan Rabe, Mathias Trabs
https://arxiv.org/abs/2508.12391 https://arxiv…

Asymptotic confidence bands for the histogram regression estimator
In a multivariate nonparametric regression model with a Hölder continuous regression function and heteroscedastic noise asymptotic uniform confidence bands are constructed based on the histogram estimator. The radius of the confidence bands does not depend on an extreme value distribution, but instead can be numerically calculated for the chosen binning.

Adam Silver says he expects big raises for WNBA players in new CBA, and that they 'deserve it' https://www.foxsports.com/articles/wnba/adam-silver-says-he-expects-big-raises-for-wnba-players-in-new-cba-and-…

On frequentist confidence intervals in a non-Gaussian regime
Shubham Barua, Shantanu Desai, Mauricio Lopez-Hernandez, Eoin \'O Colg\'ain
https://arxiv.org/abs/2508.10633

On frequentist confidence intervals in a non-Gaussian regime
We study frequentist confidence intervals based on graphical profile likelihoods (Wilks' theorem, likelihood integration), and the Feldman-Cousins (FC) prescription, a generalisation of the Neyman belt construction, in a setting with non-Gaussian Markov chain Monte Carlo (MCMC) posteriors. Our simplified setting allows us to recycle the MCMC chain as an input in all methods, including mock simulations underlying the FC approach. We find all methods agree to within $10 \%$ in the close to Gaussi…

No one has ever convinced anyone with "data" and "facts." A stakeholder will always have more confidence in their existing assumptions than in your findings.
The only way to change minds is through gradual influence that nurtures a sense of ownership.
#AI tools promise to accelerate the pace of research, but they do so only by skipping this process of sense-making. Res…

Research is a leadership skill; don't cede it to AI
The role of UX is not only to change the behaviors of users, but also to influence the behaviors of stakeholders. Adding AI tools to this process only undermines alignment.

🇺🇦 #NowPlaying on #BBC6Music's #HuwStephens
Confidence Man:
🎵 Holiday
#ConfidenceMan
https://heavenlyrecordings.bandcamp.com/track/confidence-man-holiday-bruise-remix
https://open.spotify.com/track/53wnscuzFnH8jaGymzqgfi

Analyzing Undergraduate Problem-Solving in Physics Through Interaction With an AI Chatbot
Syed Furqan Abbas Hashmi, N. Sanjay Rebello
https://arxiv.org/abs/2508.14778 https://…

Analyzing Undergraduate Problem-Solving in Physics Through Interaction With an AI Chatbot
Providing individualized scaffolding for physics problem solving at scale remains an instructional challenge. We investigate (1) students' perceptions of a Socratic Artificial Intelligence (AI) chatbot's impact on problem-solving skills and confidence and (2) how the specificity of students' questions during tutoring relates to performance. We deployed a custom Socratic AI chatbot in a large-enrollment introductory mechanics course at a Midwestern public university, logging full dialogue transc…

Beyond the Score: Uncertainty-Calibrated LLMs for Automated Essay Assessment
Ahmed Karim (Judy), Qiao Wang (Judy), Zheng Yuan
https://arxiv.org/abs/2509.15926 https://

Beyond the Score: Uncertainty-Calibrated LLMs for Automated Essay Assessment
Automated Essay Scoring (AES) systems now reach near human agreement on some public benchmarks, yet real-world adoption, especially in high-stakes examinations, remains limited. A principal obstacle is that most models output a single score without any accompanying measure of confidence or explanation. We address this gap with conformal prediction, a distribution-free wrapper that equips any classifier with set-valued outputs and formal coverage guarantees. Two open-source large language models…

🇺🇦 #NowPlaying on KEXP's #DriveTime
DJ Seinfeld & Confidence Man:
🎵 The Right
#DJSeinfeld #ConfidenceMan
https://djseinfeld.bandcamp.com/album/the-right
https://open.spotify.com/track/6Rs9a5wCEYHviyHVIMa0Eb

A Comprehensive Comparison of the Wald, Wilson, and adjusted Wilson Confidence Intervals for Proportions
Nabil Kahouadji
https://arxiv.org/abs/2508.10223 https://

A Comprehensive Comparison of the Wald, Wilson, and adjusted Wilson Confidence Intervals for Proportions
The standard confidence interval for a population proportion covered in the overwhelming majority of introductory and intermediate statistics textbooks surprisingly remains the Wald confidence interval despite having a poor coverage probability, especially for small sample sizes or when the unknown population proportion is close to either 0 or 1. Using the mean coverage probability, and for some sample sizes, Agresti and Coull showed not only that the 95\% Wilson confidence interval performs be…

Bears get strong words from NFL analyst after defeating Cowboys https://www.sportingnews.com/us/nfl/chicago-bears/news/bears-nfl-analyst-praises-cowboys-win/ca7c2b2784fd310d04076684

Overconfidence in LLM-as-a-Judge: Diagnosis and Confidence-Driven Solution
Zailong Tian, Zhuoheng Han, Yanzhe Chen, Haozhe Xu, Xi Yang, richeng xuan, Hongfeng Wang, Lizi Liao
https://arxiv.org/abs/2508.06225

Overconfidence in LLM-as-a-Judge: Diagnosis and Confidence-Driven Solution
Large Language Models (LLMs) are widely used as automated judges, where practical value depends on both accuracy and trustworthy, risk-aware judgments. Existing approaches predominantly focus on accuracy, overlooking the necessity of well-calibrated confidence, which is vital for adaptive and reliable evaluation pipelines. In this work, we advocate a shift from accuracy-centric evaluation to confidence-driven, risk-aware LLM-as-a-Judge systems, emphasizing the necessity of well-calibrated confi…

Why Jalen Hurts has increased confidence after Eagles' Super Bowl run

https://www.cbssports.com/nfl/news/why-jalen-hurts-has-increased-confidence-after-eagle…

All Roads Lead to Rome: Graph-Based Confidence Estimation for Large Language Model Reasoning
Caiqi Zhang, Chang Shu, Ehsan Shareghi, Nigel Collier
https://arxiv.org/abs/2509.12908

All Roads Lead to Rome: Graph-Based Confidence Estimation for Large Language Model Reasoning
Confidence estimation is essential for the reliable deployment of large language models (LLMs). Existing methods are primarily designed for factual QA tasks and often fail to generalize to reasoning tasks. To address this gap, we propose a set of training-free, graph-based confidence estimation methods tailored to reasoning tasks. Our approach models reasoning paths as directed graphs and estimates confidence by exploiting graph properties such as centrality, path convergence, and path weightin…

Week 4 NFL Power Rankings: 49ers, Bears rise as injuries take their toll on QBs https://www.nytimes.com/athletic/6652493/2025/09/23/nfl-power-rankings-week-4-caleb-williams-bears-49ers/

Raiders Notes: Geno Smith’s Confidence, Jordan Meredith Experiment, And More https://raiderramble.com/2025/09/17/raiders-notes-geno-smiths-confidence-jordan-meredith-experiment-and-more/

New poll: Public confidence in CDC for vaccine advice tumbles
https://www.cidrap.umn.edu/childhood-vaccines/new-poll-public-confidence-cdc-vaccine-advice-tumbles

SharpLink Gaming, the second-largest publicly traded ether treasury firm, raised $76.5M in a direct stock offering priced above market (CoinDesk)
https://www.coindesk.com/business/2025/10/16/sharplink-raises-usd76-5…

SharpLink Raises $76.5M in Premium-Priced Stock Deal to Expand Ether Holdings
The sale reflects "strong institutional confidence," the company said, with an unnamed investor also receiving an option to buy another 4.5 million shares

CountTRuCoLa: Rule Confidence Learning for Temporal Knowledge Graph Forecasting
Julia Gastinger, Christian Meilicke, Heiner Stuckenschmidt
https://arxiv.org/abs/2509.09474 https…

CountTRuCoLa: Rule Confidence Learning for Temporal Knowledge Graph Forecasting
We address the task of temporal knowledge graph (TKG) forecasting by introducing a fully explainable method based on temporal rules. Motivated by recent work proposing a strong baseline using recurrent facts, our approach learns four simple types of rules with a confidence function that considers both recency and frequency. Evaluated on nine datasets, our method matches or surpasses the performance of eight state-of-the-art models and two baselines, while providing fully interpretable predictio…

French government collapses after prime minister loses confidence vote (Saskya Vandoorne/CNN)
https://www.cnn.com/2025/09/08/europe/french-prime-minister-confidence-vote-latam-intl
http://www.memeorandum.com/250908/p83#a250908p83

Optimal Conformal Prediction, E-values, Fuzzy Prediction Sets and Subsequent Decisions
Nick W. Koning, Sam van Meer
https://arxiv.org/abs/2509.13130 https://

Optimal Conformal Prediction, E-values, Fuzzy Prediction Sets and Subsequent Decisions
We make three contributions to conformal prediction. First, we propose fuzzy conformal confidence sets that offer a degree of exclusion, generalizing beyond the binary inclusion/exclusion offered by classical confidence sets. We connect fuzzy confidence sets to e-values to show this degree of exclusion is equivalent to an exclusion at different confidence levels, capturing precisely what e-values bring to conformal prediction. We show that a fuzzy confidence set is a predictive distribution wit…

Significant inference and confidence sets for graphical models
P. A. Koldanov, A. P. Koldanov
https://arxiv.org/abs/2509.12292 https://arxiv.org/pdf/2509.1…

Significant inference and confidence sets for graphical models
The problem of identifying statistically significant inferences about the structure of the graphical model is considered, along with the related task of constructing a confidence set for a graphical model. It has been proven that the procedure for constructing such set is equivalent to the procedure for simultaneous testing of hypotheses and alternatives regarding the composition of the graphical model. Some variants of the simultaneous testing of hypotheses and alternatives are discussed. It i…

Probing Pre-trained Language Models on Code Changes: Insights from ReDef, a High-Confidence Just-in-Time Defect Prediction Dataset
Doha Nam, Taehyoun Kim, Duksan Ryu, Jongmoon Baik
https://arxiv.org/abs/2509.09192

Probing Pre-trained Language Models on Code Changes: Insights from ReDef, a High-Confidence Just-in-Time Defect Prediction Dataset
Just-in-Time software defect prediction (JIT-SDP) plays a critical role in prioritizing risky code changes during code review and continuous integration. However, existing datasets often suffer from noisy labels and low precision in identifying bug-inducing commits. To address this, we present ReDef (Revert-based Defect dataset), a high-confidence benchmark of function-level modifications curated from 22 large-scale C/C++ projects. Defective cases are anchored by revert commits, while clean cas…

🇺🇦 #NowPlaying on KEXP's #DriveTime
DJ Seinfeld & Confidence Man:
🎵 The Right
#DJSeinfeld #ConfidenceMan
https://djseinfeld.bandcamp.com/album/the-right
https://open.spotify.com/track/6Rs9a5wCEYHviyHVIMa0Eb

NFL Week 2 confidence picks: Buccaneers over Texans upset pick, plus Bears to cover vs. Lions https://www.nytimes.com/athletic/6616142/2025/09/10/nfl-week-2-confidence-picks-buccaneers-bears/

It's not often genuinely new #glaciology papers get into real @… journal - but in this one it's a welcome technial advance - IMHO we've put far too much confidence in models and satellite data - these are important but they *MUST* be supplemented with in-situ data.
This is a really smart idea. Looking forward to diving into it.
https://www.nature.com/articles/s41586-025-09347-7

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[2/8]:
- Overconfidence in LLM-as-a-Judge: Diagnosis and Confidence-Driven Solution
Zailong Tian, Zhuoheng Han, Yanzhe Chen, Haozhe Xu, Xi Yang, Richeng Xuan, Houfeng Wang, Lizi Liao

Enhancing Multi-Agent Debate System Performance via Confidence Expression
Zijie Lin, Bryan Hooi
https://arxiv.org/abs/2509.14034 https://arxiv.org/pdf/2509…

Enhancing Multi-Agent Debate System Performance via Confidence Expression
Generative Large Language Models (LLMs) have demonstrated remarkable performance across a wide range of tasks. Recent research has introduced Multi-Agent Debate (MAD) systems, which leverage multiple LLMs to simulate human debate and thereby improve task performance. However, while some LLMs may possess superior knowledge or reasoning capabilities for specific tasks, they often struggle to clearly communicate this advantage during debates, in part due to a lack of confidence expression. Moreove…

Calibration-Aware Prompt Learning for Medical Vision-Language Models
Abhishek Basu, Fahad Shamshad, Ashshak Sharifdeen, Karthik Nandakumar, Muhammad Haris Khan
https://arxiv.org/abs/2509.15226

Calibration-Aware Prompt Learning for Medical Vision-Language Models
Medical Vision-Language Models (Med-VLMs) have demonstrated remarkable performance across diverse medical imaging tasks by leveraging large-scale image-text pretraining. However, their confidence calibration is largely unexplored, and so remains a significant challenge. As such, miscalibrated predictions can lead to overconfident errors, undermining clinical trust and decision-making reliability. To address this, we introduce CalibPrompt, the first framework to calibrate Med-VLMs during prompt …

Edgington's Method for Random-Effects Meta-Analysis Part I: Estimation
David Kronthaler, Leonhard Held
https://arxiv.org/abs/2510.12301 https://arxiv.o…

Edgington's Method for Random-Effects Meta-Analysis Part I: Estimation
Meta-analysis can be formulated as combining $p$-values across studies into a joint $p$-value function, from which point estimates and confidence intervals can be derived. We extend the meta-analytic estimation framework based on combined $p$-value functions to incorporate uncertainty in heterogeneity estimation by employing a confidence distribution approach. Specifically, the confidence distribution of Edgington's method is adjusted according to the confidence distribution of the heterogeneit…

NFL Week 6 confidence picks: Dolphins, 49ers, Lions among upset picks https://www.nytimes.com/athletic/6699692/2025/10/08/nfl-week-6-confidence-picks-dolphins-49ers-lions/

Joe Milton gets important vote of confidence after struggles in Cowboys debut https://www.si.com/nfl/cowboys/news/joe-milton-gets-important-vote-of-confidence-after-struggles-dallas-cowboys-debut

Why the acting CDC director's background does not inspire confidence (Steve Benen/MSNBC)
https://www.msnbc.com/rachel-maddow-show/maddowblog/acting-cdc-directors-background-not-inspire-confidence-rcna228822
http://www.memeorandum.com/250903/p98#a250903p98

Credence Calibration Game? Calibrating Large Language Models through Structured Play
Ke Fang, Tianyi Zhao, Lu Cheng
https://arxiv.org/abs/2508.14390 https://

Credence Calibration Game? Calibrating Large Language Models through Structured Play
As Large Language Models (LLMs) are increasingly deployed in decision-critical domains, it becomes essential to ensure that their confidence estimates faithfully correspond to their actual correctness. Existing calibration methods have primarily focused on post-hoc adjustments or auxiliary model training; however, many of these approaches necessitate additional supervision or parameter updates. In this work, we propose a novel prompt-based calibration framework inspired by the Credence Calibrat…

Raiders' CB Kyu Blu Kelly Playing with Full Confidence https://www.si.com/nfl/raiders/las-vegas-kyu-blu-kelly-pete-carroll-san-francisco-49ers-patrick-graham

Conformal Prediction Meets Long-tail Classification
Shuqi Liu, Jianguo Huang, Luke Ong
https://arxiv.org/abs/2508.11345 https://arxiv.org/pdf/2508.11345

Conformal Prediction Meets Long-tail Classification
Conformal Prediction (CP) is a popular method for uncertainty quantification that converts a pretrained model's point prediction into a prediction set, with the set size reflecting the model's confidence. Although existing CP methods are guaranteed to achieve marginal coverage, they often exhibit imbalanced coverage across classes under long-tail label distributions, tending to over cover the head classes at the expense of under covering the remaining tail classes. This under coverage is partic…

The NazoNazo Benchmark: A Cost-Effective and Extensible Test of Insight-Based Reasoning in LLMs
Masaharu Mizumoto, Dat Nguyen, Zhiheng Han, Jiyuan Fang, Heyuan Guan, Xingfu Li, Naoya Shiraishi, Xuyang Tian, Yo Nakawake, Le Minh Nguyen
https://arxiv.org/abs/2509.14704

The NazoNazo Benchmark: A Cost-Effective and Extensible Test of Insight-Based Reasoning in LLMs
Benchmark saturation and contamination undermine confidence in LLM evaluation. We present Nazonazo, a cost-effective and extensible benchmark built from Japanese children's riddles to test insight-based reasoning. Items are short (mostly one sentence), require no specialized domain knowledge, and can be generated at scale, enabling rapid refresh of blind sets when leakage is suspected. We evaluate 38 frontier models and 126 adults on 120 riddles. No model except for GPT-5 is comparable to human…

Zero-Shot Robustness of Vision Language Models Via Confidence-Aware Weighting
Nikoo Naghavian, Mostafa Tavassolipour
https://arxiv.org/abs/2510.02913 https://

Zero-Shot Robustness of Vision Language Models Via Confidence-Aware Weighting
Vision-language models like CLIP demonstrate impressive zero-shot generalization but remain highly vulnerable to adversarial attacks. In this work, we propose Confidence-Aware Weighting (CAW) to enhance zero-shot robustness in vision-language models. CAW consists of two components: (1) a Confidence-Aware loss that prioritizes uncertain adversarial examples by scaling the KL divergence between clean and adversarial predictions, and (2) a feature alignment regularization that preserves semantic c…

Simultaneous Frequentist Calibration of Confidence Regions for Multiple Functionals in Constrained Inverse Problems
Pau Batlle, Pratik Patil, Michael Stanley, Javier Ruiz Lupon, Houman Owhadi, Mikael Kuusela
https://arxiv.org/abs/2510.11708

Simultaneous Frequentist Calibration of Confidence Regions for Multiple Functionals in Constrained Inverse Problems
Many scientific analyses require simultaneous comparison of multiple functionals of an unknown signal at once, calling for multidimensional confidence regions with guaranteed simultaneous frequentist under structural constraints (e.g., non-negativity, shape, or physics-based). This paper unifies and extends many previous optimization-based approaches to constrained confidence region construction in linear inverse problems through the lens of statistical test inversion. We begin by reviewing the…

NFL Week 1 confidence picks: Why the Raiders are a strong upset pick https://www.nytimes.com/athletic/6594689/2025/09/03/nfl-week-1-confidence-picks/

Confidence Intervals for Extinction Risk: Validating Population Viability Analysis with Limited Data
Hiroshi Hakoyama
https://arxiv.org/abs/2509.09965 https://

Confidence Intervals for Extinction Risk: Validating Population Viability Analysis with Limited Data
Quantitative assessment of extinction risk requires not only point estimates but also confidence intervals (CIs) that remain informative with limited data. Their reliability has been debated, as short observation spans can inflate uncertainty and reduce usefulness. I derive new CIs for extinction probability $G$ under the Wiener process with drift, a canonical model of population viability analysis. The method uses correlated noncentral-$t$ distributions for the transformed statistics $\widehat…

GrACE: A Generative Approach to Better Confidence Elicitation in Large Language Models
Zhaohan Zhang, Ziquan Liu, Ioannis Patras
https://arxiv.org/abs/2509.09438 https://…

GrACE: A Generative Approach to Better Confidence Elicitation in Large Language Models
Assessing the reliability of Large Language Models (LLMs) by confidence elicitation is a prominent approach to AI safety in high-stakes applications, such as healthcare and finance. Existing methods either require expensive computational overhead or suffer from poor calibration, making them impractical and unreliable for real-world deployment. In this work, we propose GrACE, a Generative Approach to Confidence Elicitation that enables scalable and reliable confidence elicitation for LLMs. GrACE…

'Confidence is high' for Cowboys offense heading into Panthers showdown https://www.sportingnews.com/us/nfl/dallas-cowboys/news/confidence-high-cowboys-offense-heading-panthers-showdown/2e45b9c71d568…

Better bootstrap t confidence intervals for the mean
Art B. Owen
https://arxiv.org/abs/2508.10083 https://arxiv.org/pdf/2508.10083

Better bootstrap t confidence intervals for the mean
This article explores combinations of weighted bootstraps, like the Bayesian bootstrap, with the bootstrap $t$ method for setting approximate confidence intervals for the mean of a random variable in small samples. For this problem the usual bootstrap $t$ has good coverage but provides intervals with long and highly variable lengths. Those intervals can have infinite length not just for tiny $n$, when the data have a discrete distribution. The BC$_a$ bootstrap produces shorter intervals but ten…

Carroll's Continued Confidence in Revamped Group Has Paid Off https://www.si.com/nfl/raiders/las-vegas-pete-carroll-devin-0white-elandon-roberts-tennessee-titans

QB Browning has coach's "unwavering" confidence https://www.espn.com/nfl/story/_/id/46450491/despite-struggles-qb-browning-taylor-unwavering-confidence

Doubly robust pointwise confidence intervals for a monotonic continuous treatment effect curve
Charles R. Doss
https://arxiv.org/abs/2508.08415 https://arx…

Doubly robust pointwise confidence intervals for a monotonic continuous treatment effect curve
We study nonparametric inference for the causal dose-response (or treatment effect) curve when the treatment variable is continuous rather than binary or discrete. We do this by developing doubly robust confidence intervals for the continuous treatment effect curve (at a fixed point) under the assumption that it is monotonic, based on inverting a likelihood ratio-type test. Monotonicity of the treatment effect curve is often a very natural assumption, and this assumption removes the need to cho…

Stetson Bennett dices up Cowboys' defense in preseason victory, playing with confidence and 'swagger' https://www.therams.com/news/stetson-bennett-dices-up-cowboys-defense-in-preseason-victory-playing-with-c…

Zac Taylor has 'unwavering' confidence in Jake Browning despite struggles https://www.nfl.com/news/zac-taylor-has-unwavering-confidence-in-jake-browning-despite-struggles

Confidence Regions for Multiple Outcomes, Effect Modifiers, and Other Multiple Comparisons
Paul N Zivich, Stephen R Cole, Noah Greifer, Lina M Montoya, Michael R Kosorok, Jessie K Edwards
https://arxiv.org/abs/2510.07076

Confidence Regions for Multiple Outcomes, Effect Modifiers, and Other Multiple Comparisons
In epidemiology, some have argued that multiple comparison corrections are not necessary as there is rarely interest in the universal null hypothesis. From a parameter estimation perspective, epidemiologists may still be interested in multiple parameters. In this context, standard confidence intervals are not guaranteed to provide simultaneous coverage of more than one parameter. In other words, use of confidence intervals in these cases will understate the uncertainty due to random error. To a…

Jaydon Blue's confidence only increasing with trust from coaches, Dak https://www.dallascowboys.com/news/jaydon-blue-s-confidence-only-increasing-with-trust-from-coaches-dak

Are we buying Carson Beck's reinvention? Georgia castoff is new Heisman favorite -- and maybe 2026 QB1

https://www.cbssports.com/nfl/draft/news/a

Jaydon Blue's confidence only increasing with trust from coaches, Dak https://www.dallascowboys.com/news/jaydon-blue-s-confidence-only-increasing-with-trust-from-coaches-dak

A Context-Aware Dual-Metric Framework for Confidence Estimation in Large Language Models
Mingruo Yuan, Shuyi Zhang, Ben Kao
https://arxiv.org/abs/2508.00600 https://

A Context-Aware Dual-Metric Framework for Confidence Estimation in Large Language Models
Accurate confidence estimation is essential for trustworthy large language models (LLMs) systems, as it empowers the user to determine when to trust outputs and enables reliable deployment in safety-critical applications. Current confidence estimation methods for LLMs neglect the relevance between responses and contextual information, a crucial factor in output quality evaluation, particularly in scenarios where background knowledge is provided. To bridge this gap, we propose CRUX (Context-awar…

NFL Week 4 confidence picks: Bills, Texans, Broncos, Chargers among the strongest choices https://www.nytimes.com/athletic/6657041/2025/09/24/nfl-week-4-confidence-picks-bills-texans-broncos-chargers/

Nate Thomas on 'confidence' in LT battle https://www.dallascowboys.com/news/nate-thomas-on-confidence-in-lt-battle

Bengals' Zac Taylor has 'unwavering' confidence in Jake Browning despite struggles, but other options remain

https://www.cbssports.com/nfl/news/…

Nate Thomas on 'confidence' in LT battle https://www.dallascowboys.com/news/nate-thomas-on-confidence-in-lt-battle