by Xiaohui Bei, Wenhao Wu, Shengwei Zhou We study how well simple mechanisms approximate gains from trade (GFT) in two-sided matching markets with independent buyer values and seller costs, where feasible outcomes form an arbitrary downward-closed family of matchings. This mode…

by Jason Hartline The article reviews the robust design and analysis of auctions, focusing on the predominant paradigm in the computer science literature, which quantifies robustness by the worst-case, over environments, ratio between the robust auction's performance and that o…

by Jason Hartline, Rebecca Wexler, Liren Shan, Alec Sun Prosecutors regularly rely on AI e-discovery software, known as technology assisted review (TAR) tools, to sort and prioritize digital evidence. These tools implicate constitutional concerns: they can either risk suppressi…

by Ali Asadi, Krishnendu Chatterjee, David Lurie, Raimundo Saona Partially observable Markov decision processes (POMDPs) are a central model for uncertainty in sequential decision making. The most basic objective is the reachability objective, where a target set must be eventua…

by Ioannis Anagnostides, Weiqiang Zheng A (coarse) correlated equilibrium (CE) is information-value-free (IVF) if a player can match the payoff obtained from recommendations by committing to a fixed action. Motivated by the problem of regulating algorithmic collusion, this refi…

Understanding how helpful a visualization is from experimental results is difficult because the observed performance is confounded with aspects of the study design, such as how useful the information

by Yifan Wu, Ziyang Guo, Michalis Mamakos, Jason Hartline, Jessica Hullman Understanding how helpful a visualization is from experimental results is difficult because the observed performance is confounded with aspects of the study design, such as how useful the information tha…

by Nicholas Teh Full justified representation (FJR) is among the strongest known satisfiable proportionality axioms for approval-based committee elections. Recent work has shown that an FJR committee can be found in polynomial time, but verifying whether a given committee satis…

by Louise Martin, Hijrah Nasir, Reza Bagheri, Ukadike C. Ugbolue, Catherine Laporte, Julien S. Baker, Yaodong Gu, Marek Zak, Martine Duclos, Frédéric Dutheil Abstract Background As whether the positive effects of physical activity on mortality outweigh the negative effects of e…

by Xiaohua Zhao, Youliang Zhang, Yitao Jiang, Xinchun Li, Wanglin Li Background: Diastasis recti abdominis (DRA) requires accurate ultrasound-based quantification of abdominal tissue morphology, but manual measurement is operator-dependent and inefficient for longitudinal monit…

by Sophie Greenwood, Nikhil Garg We build, deploy, and evaluate Paper Skygest, a custom personalized social feed for scientific content posted by a user's network on Bluesky and the AT Protocol. We leverage a new capability on emerging decentralized social media platforms: the…

by Jason D. Hartline, Chang Wang, Chenhao Zhang A correlated equilibrium is information-value-free if every player has an action that yields the same payoff as their equilibrium strategy when all other players follow their respective equilibrium strategies. An equilibrium is le…

by Andreas Bauer Generative artificial intelligence has reduced the cost of producing convincing artifacts of expertise-reports, analyses, proposals-to nearly zero. Signaling theory predicts that signals whose informational content rests on production cost lose that content whe…

by Giannis Fikioris, Balasubramanian Sivan, Éva Tardos The study of repeated interactions between a learner and a utility-maximizing optimizer has yielded deep insights into the manipulability of learning algorithms. However, existing literature primarily focuses on independent…

by Yining Zhang, Jiaxin Pu, Xuenan Zhuang, Xinlei Hao, Xuelin Chen, Yi He, Guanghan Zhang, Miaoling Li, Yuying Ji, Feng Wen Purpose To investigate the association between choroidal vascular hyperpermeability (CVH) and the occurrence of submacular haemorrhage (SMH) in polypoidal…

by Weili Ren, Jianan Li, Yuge Tian, Deyan Liu, Zhiduo Chen, Shangjian Yang, Jie Ren BACKGROUND: Digital inequality may be associated with health disparities in rural ageing populations, yet its cognitive and social pathways and contextual conditions remain insufficiently unders…

by Taylor J. Smith A two-dimensional automaton is able to move its input head through its input word in four directions: upward, downward, leftward, and rightward. If we prevent the input head from moving upward, then we obtain a three-way two-dimensional automaton; preventing…

by A Pranav, Vagrant Gautam, Martin Mundt, Jordan Taylor, Arjun Subramonian, Franziska Sofia Hafner, Daniel Chechelnitsky, William Agnew, Anne Lauscher In academic publishing, names connect scholars to their work. When scholars change their names, including for marriage, academ…

by Keyon Vafa, Peter G. Chang, Ashesh Rambachan, Sendhil Mullainathan Foundation models are premised on the idea that sequence prediction can uncover deeper domain understanding, much like how Kepler's predictions of planetary motion later led to the discovery of Newtonian mech…

by Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best pe…

by Rasmus Pagh, Sia Sejer We consider the problem of privately releasing a $k$-dimensional vector under updates: Starting with a zero vector, at times $t_1, t_2,\dots$ the vector is updated by adding $x^{(1)}, x^{(2)},\dots$, respectively. For positive integers $T$, $k$ we mode…

by Jérôme Adda, Marco Ottaviani Abstract The article develops a model of nonmarket allocation of resources such as the awarding of grants to meritorious projects, honors to outstanding students, or journal slots to quality publications. On the supply side, the available budget…

by Yuxuan Lu, Yifan Wu, Jason Hartline, Lunjia Hu Calibrated predictions are useful because their numerical values can be interpreted as probabilities. Calibration errors are therefore widely used to evaluate, compare, and tune probabilistic predictors. Recently, Haghtalab et a…

by Gordon V. Cormack, Maura R. Grossman Abstract Using a novel evaluation toolkit that simulates a human reviewer in the loop, we compare the effectiveness of three machine-learning protocols for technology-assisted review as used in document review for discovery in legal proce…

Attach Bluesky discussion to academic papers.

by Jason Hartline, Liren Shan, Alec Sun, Rebecca Wexler Prosecutors regularly rely on AI e-discovery software, known as technology assisted review (TAR) tools, to sort and prioritize digital evidence. These tools implicate constitutional concerns: they can either risk suppressi…

by Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Ankur Moitra, Alistair Stewart We study high-dimensional distribution learning in an agnostic setting where an adversary is allowed to arbitrarily corrupt an $\varepsilon$-fraction of the samples. Such questions have…

by Nikhil Garg, Wes Gurnee, David Rothschild, David Shmoys Every representative democracy must specify a mechanism under which voters choose their representatives. The most common mechanism in the United States -- Winner takes all single-member districts -- both enables substan…

by Alexander Matros, Constantine Sorokin We study a tractable two-player contest built on a truncated cubic contest success function. Its defining feature is a strategic-feedback parameter whose sign determines whether a leading player's effort lowers (suppression) or raises (e…

by Ashley Craig, Itai Sher Less-salient taxes can ease the classic equality-efficiency trade-off by making people respond less to taxation. But deliberately obscuring taxes may be viewed as dishonest. This creates a three-way trade-off between equality, efficiency, and honesty.…

by Janet Vertesi, danah boyd, Alex Taylor, Benjamin Shestakofsky The Project of AI is a world-building endeavor, wherein those who fund and develop AI systems both operate through and seek to sustain networks of power and wealth. As they expand their access to resources and con…

by Clément L. Canonne, Yash Pote, Jonathan Scarlett, Joy Qiping Yang We introduce the problem of \emph{entropy equivalence testing} for probability distributions, a relaxation of the well-studied closeness testing problem, where the distribution testing algorithm is now only re…

by Zhe Hou We present Isabellm, an LLM-powered theorem prover for Isabelle/HOL that performs fully automatic proof synthesis. Isabellm works with any local LLM on Ollama and APIs such as Gemini CLI, and it is designed to run on consumer grade computers. The system combines a st…

by Aviad Rubinstein, Sahil Singla We revisit three fundamental problems in algorithms under uncertainty: the Secretary Problem, Prophet Inequality, and Stochastic Probing, each subject to general downward-closed constraints. When elements have binary values, all three problems…

by Harshvardhan J. Pandit, Dick A. H. Blankvoort, Adel Shaaban, Sasha Luccioni, Abeba Birhane Generative AI services like ChatGPT and Gemini are some of the fastest-growing consumer services. Individuals using such services must accept their terms of use before access, and conf…

by Nima Haghpanah, Jason Hartline Abstract We study when pure bundling, i.e., offering only the grand bundle of all products, is optimal for a multi-product monopolist. Pure bundling is optimal if consumers with higher values for the grand bundle have higher relative values for…

by Amy Finkelstein, Matthew J Notowidigdo, Frank Schilbach, Jonathan Zhang ABSTRACT We leverage spatial variation in the severity of the Great Recession across the United States to examine its impact on mortality and explore the quantitative implications. We estimate that an in…

by Ali Falahati, Elliot Creager, Gautam Kamath, Shubhankar Mohapatra Drifting Models have emerged as a new paradigm for one-step generative modeling, achieving strong image quality without iterative inference. The premise is to replace the iterative denoising process in diffusi…

by Joydeep Biswas, Sheila Schoepp, Gautham Vasan, Anthony Opipari, Arthur Zhang, Zichao Hu, Sebastian Joseph, Matthew Lease, Junyi Jessy Li, Peter Stone, Kiri L. Wagstaff, Matthew E. Taylor, Odest Chadwicke Jenkins Scientific peer review faces mounting strain as submission volu…

by Shuchi Chawla, Jason Hartline, Robert Kleinberg Algorithmic pricing is the computational problem that sellers (e.g., in supermarkets) face when trying to set prices for their items to maximize their profit in the presence of a known demand. Guruswami et al. (2005) propose th…

by Jason D. Hartline, Tim Roughgarden Mechanism design is now a standard tool in computer science for aligning the incentives of self-interested agents with the objectives of a system designer. There is, however, a fundamental disconnect between the traditional application doma…

by Dongping Zhang, Jason Hartline, Jessica Hullman Data-driven predictions are often perceived as inaccurate in hindsight due to behavioral responses. In this study, we explore the role of interface design choices in shaping individuals' decision-making processes in response to…

by Xuefeng Xu, Graham Cormode Power transforms are popular parametric methods for making data more Gaussian-like, and are widely used as preprocessing steps in statistical analysis and machine learning. However, we find that direct implementations of power transforms suffer fro…

by Rediet Abebe, Richard Cole, Vasilis Gkatzelis, Jason D. Hartline We revisit the well-studied problem of designing mechanisms for one-sided matching markets, where a set of $n$ agents needs to be matched to a set of $n$ heterogeneous items. Each agent $i$ has a value $v_{i,j}…