Papers
Research papers from arXiv and related sources
Neural Bayesian updates to populations with growing gravitational-wave catalogs
As gravitational-wave catalogs grow, they will become increasingly computationally expensive to analyze in their entirety, especially when inferring astrophysical source populations with high-dimen...
Noah E. Wolfe, Matthew Mould, John Veitch, Salvatore Vitale
The Truthfulness Spectrum Hypothesis
Large language models (LLMs) have been reported to linearly encode truthfulness, yet recent work questions this finding's generality. We reconcile these views with the truthfulness spectrum hypothe...
Zhuofan Josh Ying, Shauli Ravfogel, Nikolaus Kriegeskorte, Peter Hase
Pseudo-Newtonian potential for accretion disks in a modified gravity spacetime around the black hole and underlying properties
We construct a pseudo-Newtonian potential (PNP) corresponding to a rotating black hole solution in a modified gravity (MGR) framework using a metric-based prescription. The motivation is to enable ...
Sriraj Chandra, Banibrata Mukhopadhyay
Tests of general relativity in pseudo-Newtonian approach
We investigate the extent to which pseudo-Newtonian gravitational potentials can reproduce classic tests of general relativity without resorting to full general relativistic formalisms. This is use...
Naman Goyal, Banibrata Mukhopadhyay, Ashish Kumar Meena
Galactic Center Gamma-Ray Excess from a Generic Triaxial Halo
Recent studies of Galactic surveys, such as Gaia, have revealed that the Milky Way's gravitational potential comes from a matter distribution that is triaxial and rotated with respect to the Galact...
Leo Qiyuan Hu, Ilias Cholis, Yi-Ming Zhong
The origin of isolated millisecond pulsars in globular clusters
A significant fraction of millisecond pulsars (MSPs) in globular clusters (GCs) are observed as isolated objects, despite the widely accepted scenario in which MSPs are formed through recycling in ...
Raniere de Menezes
The ALPINE-CRISTAL-JWST Survey: Chemical Abundance Comparison Between the ISM and CGM of Main-Sequence Galaxies at z=4-6
Gaseous halos around galaxies play an important role in galaxy evolution. The exchange of metals from the interstellar medium (ISM) to the circumgalactic medium (CGM) are caused by the formation, f...
Wuji Wang, Andreas L. Faisst, Kyle Finner, Livia Vallini, Andrea Pallottini, Enrico Veraldi, Bahr...
tttLRM: Test-Time Training for Long Context and Autoregressive 3D Reconstruction
We propose tttLRM, a novel large 3D reconstruction model that leverages a Test-Time Training (TTT) layer to enable long-context, autoregressive 3D reconstruction with linear computational complexit...
Chen Wang, Hao Tan, Wang Yifan, Zhiqin Chen, Yuheng Liu, Kalyan Sunkavalli, Sai Bi, Lingjie Liu, ...
PackFlow: Generative Molecular Crystal Structure Prediction via Reinforcement Learning Alignment
Organic molecular crystals underpin technologies ranging from pharmaceuticals to organic electronics, yet predicting solid-state packing of molecules remains challenging because candidate generatio...
Akshay Subramanian, Elton Pan, Juno Nam, Maurice Weiler, Shuhui Qu, Cheol Woo Park, Tommi S. Jaak...
Development of a Cherenkov-Based Time-of-Flight Detector Using Silicon Photomultipliers
The aim of this work is to develop high precision Time-of-Flight (TOF) devices based on high refractive index solid Cherenkov radiators read out by silicon photomultipliers (SiPMs). Cherenkov light...
Liliana Congedo, Giuseppe De Robertis, Antonio Di Mauro, Mario Giliberti, Francesco Licciulli, An...
Improving the Power of Bonferroni Adjustments under Joint Normality and Exchangeability
Bonferroni's correction is a popular tool to address multiplicity but is notorious for its low power when tests are dependent. This paper proposes a practical modification of Bonferroni's correctio...
Caleb Hiltunen, Yeonwoo Rho
ManCAR: Manifold-Constrained Latent Reasoning with Adaptive Test-Time Computation for Sequential Recommendation
Sequential recommendation increasingly employs latent multi-step reasoning to enhance test-time computation. Despite empirical gains, existing approaches largely drive intermediate reasoning states...
Kun Yang, Yuxuan Zhu, Yazhe Chen, Siyao Zheng, Bangyang Hong, Kangle Wu, Yabo Ni, Anxiang Zeng, C...
Descent-Guided Policy Gradient for Scalable Cooperative Multi-Agent Learning
Scaling cooperative multi-agent reinforcement learning (MARL) is fundamentally limited by cross-agent noise: when agents share a common reward, the actions of all $N$ agents jointly determine each ...
Shan Yang, Yang Liu
Computational Social Choice: Research & Development
Computational social choice (COMSOC) studies principled ways to aggregate conflicting individual preferences into collective decisions. In this paper, we call for an increased effort towards Comput...
Dorothea Baumeister, Ratip Emin Berker, Niclas Boehmer, Sylvain Bouveret, Andreas Darmann, Piotr ...
Conservation laws, fluxes, and symmetries: lessons from a perturbative approach for self-organized turbulence
Some turbulent flows self-organize into large-scale structures, rather than breaking up into ever-smaller scales. Underpinning this phenomenon is the existence of two sign-definite quantities which...
Anna Frishman, Sébastien Gomé, Anton Svirsky
MeanFuser: Fast One-Step Multi-Modal Trajectory Generation and Adaptive Reconstruction via MeanFlow for End-to-End Autonomous Driving
Generative models have shown great potential in trajectory planning. Recent studies demonstrate that anchor-guided generative models are effective in modeling the uncertainty of driving behaviors a...
Junli Wang, Xueyi Liu, Yinan Zheng, Zebing Xing, Pengfei Li, Guang Li, Kun Ma, Guang Chen, Hangju...
noDice: Inference for Discrete Probabilistic Programs with Nondeterminism and Conditioning
Probabilistic programming languages (PPLs) are an expressive and intuitive means of representing complex probability distributions. In that realm, languages like Dice target an important class of p...
Tobias Gürtler, Benjamin Lucien Kaminski
gencat: Generative computerized adaptive testing
Existing computerized Adaptive Testing (CAT) frameworks are typically built on predicting the correctness of a student response to a question. Although effective, this approach fails to leverage te...
Wanyong Feng, Andrew Lan
From High-Level Requirements to KPIs: Conformal Signal Temporal Logic Learning for Wireless Communications
Softwarized radio access networks (RANs), such as those based on the Open RAN (O-RAN) architecture, generate rich streams of key performance indicators (KPIs) that can be leveraged to extract actio...
Jiechen Chen, Michele Polese, Osvaldo Simeone
QUIETT: Query-Independent Table Transformation for Robust Reasoning
Real-world tables often exhibit irregular schemas, heterogeneous value formats, and implicit relational structure, which degrade the reliability of downstream table reasoning and question answering...
Gaurav Najpande, Tampu Ravi Kumar, Manan Roy Choudhury, Neha Valeti, Yanjie Fu, Vivek Gupta